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    katiapek/README.md

    Hi, I'm Kamil Kaluzny

    Python Developer | Data Engineering & Quantitative Analytics

    9+ years of engineering experience from the construction and commissioning of the Olkiluoto 3 EPR Nuclear Power Plant — from electrical supervision through team leadership (16 engineers, 150+ field staff) to I&C commissioning. Now I apply the same rigor to data pipelines, quantitative analysis, and backend development.

    What I'm Building

    Financial Analysis Terminal — a quantitative analytics platform for futures and options markets.

    • Automated data pipeline ingesting CFTC COT positioning data, CME futures prices, and options implied volatility
    • Multi-factor regime classification engine (seasonality + positioning + volatility + CTA trend signals)
    • Statistical computation layer: rolling z-scores, percentile ranks, 20/50/100/200 DMAs, ATR, Donchian channels
    • Publication-quality branded chart system with dual-resolution output
    • Comprehensive pytest suite covering data transformations, statistical calculations, and regime logic
    • Stack: Python, pandas, NumPy, SciPy, matplotlib, yfinance, CFTC APIs

    Projects

    ProjectDescriptionStackLive Demo
    Markets DashboardInteractive futures dashboard — COT reports, OHLC charts, seasonality overlays, day-trading statistics, cross-market correlationsDash, Plotly, PostgreSQL
    Time Series Bias PredictorML-powered market research app — ct-xLSTM-TS model trained on AWS EC2 GPU instancesFastAPI, PyTorch, PostgreSQL, AWS, Docker
    AutoBizOpsBusiness workflow automation with background task queues and AI-powered content generationFlask, Celery, Redis, PostgreSQL, Docker
    Expectancy CalculatorTrading strategy expectancy and Kelly Criterion calculator with interactive analysisStreamlit, PlotlyLive
    Performance VisualizerMonte Carlo simulation — 100 possible futures for any trading strategyStreamlit, Plotly, pandasLive
    Compounding SimulatorLong-term growth simulation with compounding, risk management, and drawdown analysisStreamlit, PythonLive

    Stack

    Python | pandas | NumPy | SciPy | PySpark | SQL | matplotlib | seaborn
FastAPI | Flask | SQLAlchemy | Streamlit | Celery | Redis
Dash | Plotly | PyTorch | Alembic | PostgreSQL
Docker | AWS (EC2, S3, SES, Elastic Beanstalk) | Git | GitHub Actions | Linux

    Certifications

    • Data Scientist Professional — DataCamp (2025)
    • Data Scientist Associate — DataCamp (2025)
    • Databricks Fundamentals — DataCamp (2026)
    • PySpark Fundamentals — DataCamp (2026)
    • 100 Days of Code: Python Pro Bootcamp — Dr. Angela Yu
    • Python and Flask Bootcamp — Jose Portilla / Pierian Training

    Find Me

    Pinned Loading

    1. financial-analysis-terminalfinancial-analysis-terminalPublic

      A quantitative analytics platform for futures and options markets.

      Jupyter Notebook 1

    2. autobizopsautobizopsPublic

      My micro-SaaS project for business automations.

      Python 1

    3. markets-dashboardmarkets-dashboardPublic

      Interactive futures markets dashboard with COT reports, OHLC charts, seasonality overlays, day-trading statistics, and cross-market correlation analysis.

      Python 3

    4. ts-bias-predictorts-bias-predictorPublic

      ML-powered market research app — ct-xLSTM-TS model trained on AWS EC2 GPU instances

      Python 1

    5. performance-visualizerperformance-visualizerPublic

      Monte Carlo simulation of 100 possible futures for any trading strategy.

      Python 1

    6. compounding-simulatorcompounding-simulatorPublic

      Interactive simulator for long-term compounding growth and drawdown analysis.

      Python

    , 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
     blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

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      katiapek/README.md
      Hi, I'm Kamil Kaluzny
      Python Developer | Data Engineering & Quantitative Analytics
      9+ years of engineering experience from the construction and commissioning of the Olkiluoto 3 EPR Nuclear Power Plant — from electrical supervision through team leadership (16 engineers, 150+ field staff) to I&C commissioning. Now I apply the same rigor to data pipelines, quantitative analysis, and backend development.
      What I'm Building
      Financial Analysis Terminal — a quantitative analytics platform for futures and options markets.
      • Automated data pipeline ingesting CFTC COT positioning data, CME futures prices, and options implied volatility
      • Multi-factor regime classification engine (seasonality + positioning + volatility + CTA trend signals)
      • Statistical computation layer: rolling z-scores, percentile ranks, 20/50/100/200 DMAs, ATR, Donchian channels
      • Publication-quality branded chart system with dual-resolution output
      • Comprehensive pytest suite covering data transformations, statistical calculations, and regime logic
      • Stack: Python, pandas, NumPy, SciPy, matplotlib, yfinance, CFTC APIs
      Projects
      ProjectDescriptionStackLive Demo
      Markets DashboardInteractive futures dashboard — COT reports, OHLC charts, seasonality overlays, day-trading statistics, cross-market correlationsDash, Plotly, PostgreSQL
      Time Series Bias PredictorML-powered market research app — ct-xLSTM-TS model trained on AWS EC2 GPU instancesFastAPI, PyTorch, PostgreSQL, AWS, Docker
      AutoBizOpsBusiness workflow automation with background task queues and AI-powered content generationFlask, Celery, Redis, PostgreSQL, Docker
      Expectancy CalculatorTrading strategy expectancy and Kelly Criterion calculator with interactive analysisStreamlit, PlotlyLive
      Performance VisualizerMonte Carlo simulation — 100 possible futures for any trading strategyStreamlit, Plotly, pandasLive
      Compounding SimulatorLong-term growth simulation with compounding, risk management, and drawdown analysisStreamlit, PythonLive
      Stack
      Python | pandas | NumPy | SciPy | PySpark | SQL | matplotlib | seaborn
FastAPI | Flask | SQLAlchemy | Streamlit | Celery | Redis
Dash | Plotly | PyTorch | Alembic | PostgreSQL
Docker | AWS (EC2, S3, SES, Elastic Beanstalk) | Git | GitHub Actions | Linux

      Certifications
      • Data Scientist Professional — DataCamp (2025)
      • Data Scientist Associate — DataCamp (2025)
      • Databricks Fundamentals — DataCamp (2026)
      • PySpark Fundamentals — DataCamp (2026)
      • 100 Days of Code: Python Pro Bootcamp — Dr. Angela Yu
      • Python and Flask Bootcamp — Jose Portilla / Pierian Training
      Find Me
      
Pinned
Loading
      1. financial-analysis-terminalfinancial-analysis-terminalPublic
        
A quantitative analytics platform for futures and options markets.

        Jupyter Notebook
1

      2. autobizopsautobizopsPublic
        
My micro-SaaS project for business automations.

        Python
1

      3. markets-dashboardmarkets-dashboardPublic
        
Interactive futures markets dashboard with COT reports, OHLC charts, seasonality overlays, day-trading statistics, and cross-market correlation analysis.

        Python
3

      4. ts-bias-predictorts-bias-predictorPublic
        
ML-powered market research app — ct-xLSTM-TS model trained on AWS EC2 GPU instances

        Python
1

      5. performance-visualizerperformance-visualizerPublic
        
Monte Carlo simulation of 100 possible futures for any trading strategy.

        Python
1

      6. compounding-simulatorcompounding-simulatorPublic
        
Interactive simulator for long-term compounding growth and drawdown analysis.

        Python
      
, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

      Skip to content
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 · 1
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Block or report katiapek

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        katiapek/README.md
        Hi, I'm Kamil Kaluzny
        Python Developer | Data Engineering & Quantitative Analytics
        9+ years of engineering experience from the construction and commissioning of the Olkiluoto 3 EPR Nuclear Power Plant — from electrical supervision through team leadership (16 engineers, 150+ field staff) to I&C commissioning. Now I apply the same rigor to data pipelines, quantitative analysis, and backend development.
        What I'm Building
        Financial Analysis Terminal — a quantitative analytics platform for futures and options markets.
        • Automated data pipeline ingesting CFTC COT positioning data, CME futures prices, and options implied volatility
        • Multi-factor regime classification engine (seasonality + positioning + volatility + CTA trend signals)
        • Statistical computation layer: rolling z-scores, percentile ranks, 20/50/100/200 DMAs, ATR, Donchian channels
        • Publication-quality branded chart system with dual-resolution output
        • Comprehensive pytest suite covering data transformations, statistical calculations, and regime logic
        • Stack: Python, pandas, NumPy, SciPy, matplotlib, yfinance, CFTC APIs
        Projects
        ProjectDescriptionStackLive Demo
        Markets DashboardInteractive futures dashboard — COT reports, OHLC charts, seasonality overlays, day-trading statistics, cross-market correlationsDash, Plotly, PostgreSQL
        Time Series Bias PredictorML-powered market research app — ct-xLSTM-TS model trained on AWS EC2 GPU instancesFastAPI, PyTorch, PostgreSQL, AWS, Docker
        AutoBizOpsBusiness workflow automation with background task queues and AI-powered content generationFlask, Celery, Redis, PostgreSQL, Docker
        Expectancy CalculatorTrading strategy expectancy and Kelly Criterion calculator with interactive analysisStreamlit, PlotlyLive
        Performance VisualizerMonte Carlo simulation — 100 possible futures for any trading strategyStreamlit, Plotly, pandasLive
        Compounding SimulatorLong-term growth simulation with compounding, risk management, and drawdown analysisStreamlit, PythonLive
        Stack
        Python | pandas | NumPy | SciPy | PySpark | SQL | matplotlib | seaborn
FastAPI | Flask | SQLAlchemy | Streamlit | Celery | Redis
Dash | Plotly | PyTorch | Alembic | PostgreSQL
Docker | AWS (EC2, S3, SES, Elastic Beanstalk) | Git | GitHub Actions | Linux

        Certifications
        • Data Scientist Professional — DataCamp (2025)
        • Data Scientist Associate — DataCamp (2025)
        • Databricks Fundamentals — DataCamp (2026)
        • PySpark Fundamentals — DataCamp (2026)
        • 100 Days of Code: Python Pro Bootcamp — Dr. Angela Yu
        • Python and Flask Bootcamp — Jose Portilla / Pierian Training
        Find Me
        
Pinned
Loading
        1. financial-analysis-terminalfinancial-analysis-terminalPublic
          
A quantitative analytics platform for futures and options markets.

          Jupyter Notebook
1

        2. autobizopsautobizopsPublic
          
My micro-SaaS project for business automations.

          Python
1

        3. markets-dashboardmarkets-dashboardPublic
          
Interactive futures markets dashboard with COT reports, OHLC charts, seasonality overlays, day-trading statistics, and cross-market correlation analysis.

          Python
3

        4. ts-bias-predictorts-bias-predictorPublic
          
ML-powered market research app — ct-xLSTM-TS model trained on AWS EC2 GPU instances

          Python
1

        5. performance-visualizerperformance-visualizerPublic
          
Monte Carlo simulation of 100 possible futures for any trading strategy.

          Python
1

        6. compounding-simulatorcompounding-simulatorPublic
          
Interactive simulator for long-term compounding growth and drawdown analysis.

          Python
        
, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

        Skip to content
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 · 1
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          katiapek/README.md
          Hi, I'm Kamil Kaluzny
          Python Developer | Data Engineering & Quantitative Analytics
          9+ years of engineering experience from the construction and commissioning of the Olkiluoto 3 EPR Nuclear Power Plant — from electrical supervision through team leadership (16 engineers, 150+ field staff) to I&C commissioning. Now I apply the same rigor to data pipelines, quantitative analysis, and backend development.
          What I'm Building
          Financial Analysis Terminal — a quantitative analytics platform for futures and options markets.
          • Automated data pipeline ingesting CFTC COT positioning data, CME futures prices, and options implied volatility
          • Multi-factor regime classification engine (seasonality + positioning + volatility + CTA trend signals)
          • Statistical computation layer: rolling z-scores, percentile ranks, 20/50/100/200 DMAs, ATR, Donchian channels
          • Publication-quality branded chart system with dual-resolution output
          • Comprehensive pytest suite covering data transformations, statistical calculations, and regime logic
          • Stack: Python, pandas, NumPy, SciPy, matplotlib, yfinance, CFTC APIs
          Projects
          ProjectDescriptionStackLive Demo
          Markets DashboardInteractive futures dashboard — COT reports, OHLC charts, seasonality overlays, day-trading statistics, cross-market correlationsDash, Plotly, PostgreSQL
          Time Series Bias PredictorML-powered market research app — ct-xLSTM-TS model trained on AWS EC2 GPU instancesFastAPI, PyTorch, PostgreSQL, AWS, Docker
          AutoBizOpsBusiness workflow automation with background task queues and AI-powered content generationFlask, Celery, Redis, PostgreSQL, Docker
          Expectancy CalculatorTrading strategy expectancy and Kelly Criterion calculator with interactive analysisStreamlit, PlotlyLive
          Performance VisualizerMonte Carlo simulation — 100 possible futures for any trading strategyStreamlit, Plotly, pandasLive
          Compounding SimulatorLong-term growth simulation with compounding, risk management, and drawdown analysisStreamlit, PythonLive
          Stack
          Python | pandas | NumPy | SciPy | PySpark | SQL | matplotlib | seaborn
FastAPI | Flask | SQLAlchemy | Streamlit | Celery | Redis
Dash | Plotly | PyTorch | Alembic | PostgreSQL
Docker | AWS (EC2, S3, SES, Elastic Beanstalk) | Git | GitHub Actions | Linux

          Certifications
          • Data Scientist Professional — DataCamp (2025)
          • Data Scientist Associate — DataCamp (2025)
          • Databricks Fundamentals — DataCamp (2026)
          • PySpark Fundamentals — DataCamp (2026)
          • 100 Days of Code: Python Pro Bootcamp — Dr. Angela Yu
          • Python and Flask Bootcamp — Jose Portilla / Pierian Training
          Find Me
          
Pinned
Loading
          1. financial-analysis-terminalfinancial-analysis-terminalPublic
            
A quantitative analytics platform for futures and options markets.

            Jupyter Notebook
1

          2. autobizopsautobizopsPublic
            
My micro-SaaS project for business automations.

            Python
1

          3. markets-dashboardmarkets-dashboardPublic
            
Interactive futures markets dashboard with COT reports, OHLC charts, seasonality overlays, day-trading statistics, and cross-market correlation analysis.

            Python
3

          4. ts-bias-predictorts-bias-predictorPublic
            
ML-powered market research app — ct-xLSTM-TS model trained on AWS EC2 GPU instances

            Python
1

          5. performance-visualizerperformance-visualizerPublic
            
Monte Carlo simulation of 100 possible futures for any trading strategy.

            Python
1

          6. compounding-simulatorcompounding-simulatorPublic
            
Interactive simulator for long-term compounding growth and drawdown analysis.

            Python
          
, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

          Skip to content
          View katiapek's full-sized avatar
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          Focusing
          🎯
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Block or report katiapek

            Block user
            
Prevent this user from interacting with your repositories and sending you notifications.
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            Report abuse
            katiapek/README.md
            Hi, I'm Kamil Kaluzny
            Python Developer | Data Engineering & Quantitative Analytics
            9+ years of engineering experience from the construction and commissioning of the Olkiluoto 3 EPR Nuclear Power Plant — from electrical supervision through team leadership (16 engineers, 150+ field staff) to I&C commissioning. Now I apply the same rigor to data pipelines, quantitative analysis, and backend development.
            What I'm Building
            Financial Analysis Terminal — a quantitative analytics platform for futures and options markets.
            • Automated data pipeline ingesting CFTC COT positioning data, CME futures prices, and options implied volatility
            • Multi-factor regime classification engine (seasonality + positioning + volatility + CTA trend signals)
            • Statistical computation layer: rolling z-scores, percentile ranks, 20/50/100/200 DMAs, ATR, Donchian channels
            • Publication-quality branded chart system with dual-resolution output
            • Comprehensive pytest suite covering data transformations, statistical calculations, and regime logic
            • Stack: Python, pandas, NumPy, SciPy, matplotlib, yfinance, CFTC APIs
            Projects
            ProjectDescriptionStackLive Demo
            Markets DashboardInteractive futures dashboard — COT reports, OHLC charts, seasonality overlays, day-trading statistics, cross-market correlationsDash, Plotly, PostgreSQL
            Time Series Bias PredictorML-powered market research app — ct-xLSTM-TS model trained on AWS EC2 GPU instancesFastAPI, PyTorch, PostgreSQL, AWS, Docker
            AutoBizOpsBusiness workflow automation with background task queues and AI-powered content generationFlask, Celery, Redis, PostgreSQL, Docker
            Expectancy CalculatorTrading strategy expectancy and Kelly Criterion calculator with interactive analysisStreamlit, PlotlyLive
            Performance VisualizerMonte Carlo simulation — 100 possible futures for any trading strategyStreamlit, Plotly, pandasLive
            Compounding SimulatorLong-term growth simulation with compounding, risk management, and drawdown analysisStreamlit, PythonLive
            Stack
            Python | pandas | NumPy | SciPy | PySpark | SQL | matplotlib | seaborn
FastAPI | Flask | SQLAlchemy | Streamlit | Celery | Redis
Dash | Plotly | PyTorch | Alembic | PostgreSQL
Docker | AWS (EC2, S3, SES, Elastic Beanstalk) | Git | GitHub Actions | Linux

            Certifications
            • Data Scientist Professional — DataCamp (2025)
            • Data Scientist Associate — DataCamp (2025)
            • Databricks Fundamentals — DataCamp (2026)
            • PySpark Fundamentals — DataCamp (2026)
            • 100 Days of Code: Python Pro Bootcamp — Dr. Angela Yu
            • Python and Flask Bootcamp — Jose Portilla / Pierian Training
            Find Me
            
Pinned
Loading
            1. financial-analysis-terminalfinancial-analysis-terminalPublic
              
A quantitative analytics platform for futures and options markets.

              Jupyter Notebook
1

            2. autobizopsautobizopsPublic
              
My micro-SaaS project for business automations.

              Python
1

            3. markets-dashboardmarkets-dashboardPublic
              
Interactive futures markets dashboard with COT reports, OHLC charts, seasonality overlays, day-trading statistics, and cross-market correlation analysis.

              Python
3

            4. ts-bias-predictorts-bias-predictorPublic
              
ML-powered market research app — ct-xLSTM-TS model trained on AWS EC2 GPU instances

              Python
1

            5. performance-visualizerperformance-visualizerPublic
              
Monte Carlo simulation of 100 possible futures for any trading strategy.

              Python
1

            6. compounding-simulatorcompounding-simulatorPublic
              
Interactive simulator for long-term compounding growth and drawdown analysis.

              Python
            
, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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              katiapek/README.md
              Hi, I'm Kamil Kaluzny
              Python Developer | Data Engineering & Quantitative Analytics
              9+ years of engineering experience from the construction and commissioning of the Olkiluoto 3 EPR Nuclear Power Plant — from electrical supervision through team leadership (16 engineers, 150+ field staff) to I&C commissioning. Now I apply the same rigor to data pipelines, quantitative analysis, and backend development.
              What I'm Building
              Financial Analysis Terminal — a quantitative analytics platform for futures and options markets.
              • Automated data pipeline ingesting CFTC COT positioning data, CME futures prices, and options implied volatility
              • Multi-factor regime classification engine (seasonality + positioning + volatility + CTA trend signals)
              • Statistical computation layer: rolling z-scores, percentile ranks, 20/50/100/200 DMAs, ATR, Donchian channels
              • Publication-quality branded chart system with dual-resolution output
              • Comprehensive pytest suite covering data transformations, statistical calculations, and regime logic
              • Stack: Python, pandas, NumPy, SciPy, matplotlib, yfinance, CFTC APIs
              Projects
              ProjectDescriptionStackLive Demo
              Markets DashboardInteractive futures dashboard — COT reports, OHLC charts, seasonality overlays, day-trading statistics, cross-market correlationsDash, Plotly, PostgreSQL
              Time Series Bias PredictorML-powered market research app — ct-xLSTM-TS model trained on AWS EC2 GPU instancesFastAPI, PyTorch, PostgreSQL, AWS, Docker
              AutoBizOpsBusiness workflow automation with background task queues and AI-powered content generationFlask, Celery, Redis, PostgreSQL, Docker
              Expectancy CalculatorTrading strategy expectancy and Kelly Criterion calculator with interactive analysisStreamlit, PlotlyLive
              Performance VisualizerMonte Carlo simulation — 100 possible futures for any trading strategyStreamlit, Plotly, pandasLive
              Compounding SimulatorLong-term growth simulation with compounding, risk management, and drawdown analysisStreamlit, PythonLive
              Stack
              Python | pandas | NumPy | SciPy | PySpark | SQL | matplotlib | seaborn
FastAPI | Flask | SQLAlchemy | Streamlit | Celery | Redis
Dash | Plotly | PyTorch | Alembic | PostgreSQL
Docker | AWS (EC2, S3, SES, Elastic Beanstalk) | Git | GitHub Actions | Linux

              Certifications
              • Data Scientist Professional — DataCamp (2025)
              • Data Scientist Associate — DataCamp (2025)
              • Databricks Fundamentals — DataCamp (2026)
              • PySpark Fundamentals — DataCamp (2026)
              • 100 Days of Code: Python Pro Bootcamp — Dr. Angela Yu
              • Python and Flask Bootcamp — Jose Portilla / Pierian Training
              Find Me
              
Pinned
Loading
              1. financial-analysis-terminalfinancial-analysis-terminalPublic
                
A quantitative analytics platform for futures and options markets.

                Jupyter Notebook
1

              2. autobizopsautobizopsPublic
                
My micro-SaaS project for business automations.

                Python
1

              3. markets-dashboardmarkets-dashboardPublic
                
Interactive futures markets dashboard with COT reports, OHLC charts, seasonality overlays, day-trading statistics, and cross-market correlation analysis.

                Python
3

              4. ts-bias-predictorts-bias-predictorPublic
                
ML-powered market research app — ct-xLSTM-TS model trained on AWS EC2 GPU instances

                Python
1

              5. performance-visualizerperformance-visualizerPublic
                
Monte Carlo simulation of 100 possible futures for any trading strategy.

                Python
1

              6. compounding-simulatorcompounding-simulatorPublic
                
Interactive simulator for long-term compounding growth and drawdown analysis.

                Python
              
, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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                katiapek/README.md
                Hi, I'm Kamil Kaluzny
                Python Developer | Data Engineering & Quantitative Analytics
                9+ years of engineering experience from the construction and commissioning of the Olkiluoto 3 EPR Nuclear Power Plant — from electrical supervision through team leadership (16 engineers, 150+ field staff) to I&C commissioning. Now I apply the same rigor to data pipelines, quantitative analysis, and backend development.
                What I'm Building
                Financial Analysis Terminal — a quantitative analytics platform for futures and options markets.
                • Automated data pipeline ingesting CFTC COT positioning data, CME futures prices, and options implied volatility
                • Multi-factor regime classification engine (seasonality + positioning + volatility + CTA trend signals)
                • Statistical computation layer: rolling z-scores, percentile ranks, 20/50/100/200 DMAs, ATR, Donchian channels
                • Publication-quality branded chart system with dual-resolution output
                • Comprehensive pytest suite covering data transformations, statistical calculations, and regime logic
                • Stack: Python, pandas, NumPy, SciPy, matplotlib, yfinance, CFTC APIs
                Projects
                ProjectDescriptionStackLive Demo
                Markets DashboardInteractive futures dashboard — COT reports, OHLC charts, seasonality overlays, day-trading statistics, cross-market correlationsDash, Plotly, PostgreSQL
                Time Series Bias PredictorML-powered market research app — ct-xLSTM-TS model trained on AWS EC2 GPU instancesFastAPI, PyTorch, PostgreSQL, AWS, Docker
                AutoBizOpsBusiness workflow automation with background task queues and AI-powered content generationFlask, Celery, Redis, PostgreSQL, Docker
                Expectancy CalculatorTrading strategy expectancy and Kelly Criterion calculator with interactive analysisStreamlit, PlotlyLive
                Performance VisualizerMonte Carlo simulation — 100 possible futures for any trading strategyStreamlit, Plotly, pandasLive
                Compounding SimulatorLong-term growth simulation with compounding, risk management, and drawdown analysisStreamlit, PythonLive
                Stack
                Python | pandas | NumPy | SciPy | PySpark | SQL | matplotlib | seaborn
FastAPI | Flask | SQLAlchemy | Streamlit | Celery | Redis
Dash | Plotly | PyTorch | Alembic | PostgreSQL
Docker | AWS (EC2, S3, SES, Elastic Beanstalk) | Git | GitHub Actions | Linux

                Certifications
                • Data Scientist Professional — DataCamp (2025)
                • Data Scientist Associate — DataCamp (2025)
                • Databricks Fundamentals — DataCamp (2026)
                • PySpark Fundamentals — DataCamp (2026)
                • 100 Days of Code: Python Pro Bootcamp — Dr. Angela Yu
                • Python and Flask Bootcamp — Jose Portilla / Pierian Training
                Find Me
                
Pinned
Loading
                1. financial-analysis-terminalfinancial-analysis-terminalPublic
                  
A quantitative analytics platform for futures and options markets.

                  Jupyter Notebook
1

                2. autobizopsautobizopsPublic
                  
My micro-SaaS project for business automations.

                  Python
1

                3. markets-dashboardmarkets-dashboardPublic
                  
Interactive futures markets dashboard with COT reports, OHLC charts, seasonality overlays, day-trading statistics, and cross-market correlation analysis.

                  Python
3

                4. ts-bias-predictorts-bias-predictorPublic
                  
ML-powered market research app — ct-xLSTM-TS model trained on AWS EC2 GPU instances

                  Python
1

                5. performance-visualizerperformance-visualizerPublic
                  
Monte Carlo simulation of 100 possible futures for any trading strategy.

                  Python
1

                6. compounding-simulatorcompounding-simulatorPublic
                  
Interactive simulator for long-term compounding growth and drawdown analysis.

                  Python
                
, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

                Skip to content
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                🎯
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                🎯
                Focusing
                1
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 · 1
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Block or report katiapek

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                  katiapek/README.md
                  Hi, I'm Kamil Kaluzny
                  Python Developer | Data Engineering & Quantitative Analytics
                  9+ years of engineering experience from the construction and commissioning of the Olkiluoto 3 EPR Nuclear Power Plant — from electrical supervision through team leadership (16 engineers, 150+ field staff) to I&C commissioning. Now I apply the same rigor to data pipelines, quantitative analysis, and backend development.
                  What I'm Building
                  Financial Analysis Terminal — a quantitative analytics platform for futures and options markets.
                  • Automated data pipeline ingesting CFTC COT positioning data, CME futures prices, and options implied volatility
                  • Multi-factor regime classification engine (seasonality + positioning + volatility + CTA trend signals)
                  • Statistical computation layer: rolling z-scores, percentile ranks, 20/50/100/200 DMAs, ATR, Donchian channels
                  • Publication-quality branded chart system with dual-resolution output
                  • Comprehensive pytest suite covering data transformations, statistical calculations, and regime logic
                  • Stack: Python, pandas, NumPy, SciPy, matplotlib, yfinance, CFTC APIs
                  Projects
                  ProjectDescriptionStackLive Demo
                  Markets DashboardInteractive futures dashboard — COT reports, OHLC charts, seasonality overlays, day-trading statistics, cross-market correlationsDash, Plotly, PostgreSQL
                  Time Series Bias PredictorML-powered market research app — ct-xLSTM-TS model trained on AWS EC2 GPU instancesFastAPI, PyTorch, PostgreSQL, AWS, Docker
                  AutoBizOpsBusiness workflow automation with background task queues and AI-powered content generationFlask, Celery, Redis, PostgreSQL, Docker
                  Expectancy CalculatorTrading strategy expectancy and Kelly Criterion calculator with interactive analysisStreamlit, PlotlyLive
                  Performance VisualizerMonte Carlo simulation — 100 possible futures for any trading strategyStreamlit, Plotly, pandasLive
                  Compounding SimulatorLong-term growth simulation with compounding, risk management, and drawdown analysisStreamlit, PythonLive
                  Stack
                  Python | pandas | NumPy | SciPy | PySpark | SQL | matplotlib | seaborn
FastAPI | Flask | SQLAlchemy | Streamlit | Celery | Redis
Dash | Plotly | PyTorch | Alembic | PostgreSQL
Docker | AWS (EC2, S3, SES, Elastic Beanstalk) | Git | GitHub Actions | Linux

                  Certifications
                  • Data Scientist Professional — DataCamp (2025)
                  • Data Scientist Associate — DataCamp (2025)
                  • Databricks Fundamentals — DataCamp (2026)
                  • PySpark Fundamentals — DataCamp (2026)
                  • 100 Days of Code: Python Pro Bootcamp — Dr. Angela Yu
                  • Python and Flask Bootcamp — Jose Portilla / Pierian Training
                  Find Me
                  
Pinned
Loading
                  1. financial-analysis-terminalfinancial-analysis-terminalPublic
                    
A quantitative analytics platform for futures and options markets.

                    Jupyter Notebook
1

                  2. autobizopsautobizopsPublic
                    
My micro-SaaS project for business automations.

                    Python
1

                  3. markets-dashboardmarkets-dashboardPublic
                    
Interactive futures markets dashboard with COT reports, OHLC charts, seasonality overlays, day-trading statistics, and cross-market correlation analysis.

                    Python
3

                  4. ts-bias-predictorts-bias-predictorPublic
                    
ML-powered market research app — ct-xLSTM-TS model trained on AWS EC2 GPU instances

                    Python
1

                  5. performance-visualizerperformance-visualizerPublic
                    
Monte Carlo simulation of 100 possible futures for any trading strategy.

                    Python
1

                  6. compounding-simulatorcompounding-simulatorPublic
                    
Interactive simulator for long-term compounding growth and drawdown analysis.

                    Python