Siddarth Gopalakrishnan

Background

About Siddarth Gopalakrishnan

Data Science & Business Analytics professional with 4+ years of industry experience spanning e-commerce, marketing, public sector, and healthcare analytics. I specialize in translating business problems into data-driven solutions using predictive modeling, marketing mix modeling, A/B testing, and machine learning techniques to drive measurable impact.I’ve developed and deployed end-to-end analytical solutions, including campaign optimization models that increased marketing ROI, uplift modeling frameworks that reduced CAC by 20%, and predictive segmentation that informed targeted outreach. My experience covers the full data lifecycle from building scalable ETL pipelines and data wrangling to interactive dashboarding and communicating insights to business stakeholders.I’m known for my ability to work cross-functionally with engineering, marketing, operations, and leadership teams. I enjoy solving real-world problems using SQL, Python, and cloud tools (AWS, Azure), while delivering actionable dashboards via Power BI and Tableau. I also bring research-backed expertise from academic projects involving CatBoost classification, time series forecasting, and socio-economic impact modeling. Technical Proficiency:• Tools: Power BI, Tableau, Streamlit, Jupyter, Excel, Git, Docker, Jira, Azure Synapse, AWS (Athena, S3, Glue, Redshift), Snowflake, dbt, Apache Airflow• Languages: Python (Pandas, NumPy, SciPy, scikit-learn), SQL (MySQL, PostgreSQL, SQL Server), R• Techniques: A/B Testing, Regression, Clustering (K-Means, RFM), Time Series Forecasting, NLP, SHAP Explainability, XGBoost, CatBoost• Focus Areas: Marketing Mix Modeling Campaign Optimization, Predictive Analytics, Data Engineering, Healthcare Data, ConsultingI thrive in collaborative environments where data can shape strategy, and I'm actively exploring full-time opportunities to use my skills to solve impactful problems at scale.