Santhosh S

Results-driven Data Analyst specializing in Life Sciences and Pharmaceuticals, with expertise in SQL, Python, and Power BI. Proficient in data extraction, cleaning, and exploratory analysis, with a proven track record of developing stakeholder-ready dashboards that transform complex healthcare and sales data into clear KPIs and actionable insights. Demonstrated proficiency in AI-enabled analytics tools, including AutoML/PyCaret for rapid modeling, SHAP for enhanced explainability, and MLflow for meticulous experiment tracking. Committed to leveraging domain knowledge alongside reproducible analytics to deliver reliable forecasts and compelling executive narratives that drive strategic decision-making.

• Python Programming — Microsoft
• Power BI — Microsoft
• Machine Learning in Python — Coursera

Drug Performance & Market Share Analysis (Manual Data Analysis) 

• Analyzed multi-drug sales data to evaluate market share, growth %, prescription volume, and  regional sales penetration.

• Built Python pipelines for cleaning and descriptive statistics, reducing data preparation time by  30%.  

• Created Power BI dashboards summarizing top 5 drugs driving 75% of sales and highlighting  underperforming SKUs. 

• Insights supported optimized sales strategy and improved regional targeting accuracy by ~18%.  

Tools: Python (Pandas), Excel, Power BI, SQL

Clinical Trial Outcome Prediction & Risk Analysis (AI-Powered Data Analysis)  

• Developed predictive model to estimate Phase II to Phase III trial success probability. 

• Using patient  demographics, biomarkers, and adverse event history.

• Leveraged AutoML (PyCaret) to test 10+ algorithms, achieving ROC-AUC 0.86 and F1-score 0.79.  

• Applied SHAP to explain model drivers and identified 3 key biomarkers influencing success rates.  

• Used MLflow for experiment tracking; reproducibility improvements cut re-run time by 40%. 

Tools: Python (Pandas, scikit-learn, PyCaret), SHAP, MLflow, SQL