
Data Scientist with 5+ years of experience using SQL, Python, experimentation, and statistical analysis to solve challenging product and business problems. Expertise in metric design, hypothesis testing, causal analysis, and transforming messy, disparate datasets spanning 1M+ to over 1B records into insights, dashboards, and recommendations that influence roadmap, growth, and customer experience. Experienced in partnering closely with Product, Engineering, and Business teams.
Product Analytics: Experiment Design (A/B Testing, Multivariate Testing), Metric Design (KPIs, North Star), Hypothesis Testing, Regression, Segmentation, Statistical Analysis, Funnel Analysis, Time Series Analysis, Dashboarding, Causal Inference, User Journey Analysis
Programming / Querying: Python (NumPy, Pandas, SciPy, scikit-learn, PyTorch), PySpark, C/C, SQL
Data Engineering: Spark, Databricks, PostgreSQL, ETL/ELT, Data Modeling, Data Lakes, Data Warehouses
Data Analysis / BI: Exploratory Data Analysis (EDA), Tableau, Power BI, Excel, BigQuery
Machine Learning (ML)/Generative AI (Gen AI): Feature Engineering, Predictive Modeling, Classification, Clustering, Model Evaluation/Validation, Supervised/Unsupervised Learning, NLP, MLOps, Retrieval-Augmented Generation (RAG), Prompt Engineering, Agentic Workflows, LLM Evaluation
Cloud/DevOps Tools: Azure, AWS, Docker, Git, CI/CD, REST APIs
Collaboration Tools: Agile/Scrum, Jira, Confluence, Slack