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Sendhil0kumar/README.md

👋 Hi, I’m Sendhil Kumar

I work at the intersection of business, analytics, and execution.

With 19+ years of domain experience across Finance, HR, and Learning & Development,
I build applied business analytics solutions that focus on decision-making and impact, not just models.

🔍 What I Focus On

  • Translating business problems into analytical questions
  • Using data to support real business decisions
  • Building solutions that stakeholders can actually use

📊 Focus Areas

  • Business & Decision Analytics
  • FP&A Analytics & Forecasting
  • Marketing Analytics (Causal / Uplift Modeling)
  • HR & Workforce Analytics
  • Learning Analytics & Impact Measurement

🧰 Tools & Technologies

  • Python: Pandas, NumPy, Scikit-learn
  • Machine Learning: XGBoost, Random Forest, Causal Inference
  • Time Series: Facebook Prophet
  • Visualization: Power BI, Excel
  • Data: SQL

📌 Selected Projects

(See pinned repositories below)

  • Intelligent FP&A Command Center
    Automation, forecasting, decision support

  • Marketing Uplift Modeling
    Causal analytics for ROI optimization

  • HR Attrition & L&D Analytics
    Linking learning interventions to retention outcomes

🔗 Connect

Pinned Loading

  1. HR-Attrition-Analytics_L-D_projectHR-Attrition-Analytics_L-D_projectPublic

    An end-to-end EDA project on HR attrition data to analyze the impact of L&D programs.

  2. LendingClub-Loan-Default-PredictionLendingClub-Loan-Default-PredictionPublic

    ML project to predict loan defaults on the LendingClub dataset

  3. NLP-Sentiment-AnalysisNLP-Sentiment-AnalysisPublic

    Sentiment analysis of product reviews using classic ML models and a Recurrent Neural Network (RNN) in Python.

    Jupyter Notebook

  4. Deep-learning-drug-predictionDeep-learning-drug-predictionPublic

    Deep Learning: Comparing DNN (Fingerprints) and GNN (Graphs) for predicting drug ratings (1-10) from molecular structure

    Jupyter Notebook

  5. Intelligent-FPA-Command-CenterIntelligent-FPA-Command-CenterPublic

    End-to-end Financial Planning & Analysis (FP&A) pipeline using Python (PVM Logic, Forecasting) and Power BI

    Jupyter Notebook

  6. marketing-uplift-modelingmarketing-uplift-modelingPublic

    Optimizing Campaign ROI using XGBoost and CausalML (T-Learner)

    Jupyter Notebook