Skills
Languages & Scripting: Python (Pandas, NumPy, Matplotlib, Seaborn, Plotly, Scikit-learn), R, SQL, HiveQL, SparkSQL, Bash
Data Visualization: Power BI, Tableau, Looker Studio, Apache Superset, Matplotlib, Seaborn, Plotly Dash
Databases & Querying: MySQL, PostgreSQL, AWS RDS, MongoDB, Snowflake, HBase, Hive
Big Data & Cloud Platforms: AWS (S3, EMR, EC2, RDS, SageMaker), Hadoop (HDFS, MapReduce), Apache Spark, Pig
Machine Learning & Statistics: Regression (Linear, Logistic), Decision Tree, Random Forest, XGBoost, SVM, Time Series, PCA, A/B Testing, Hypothesis Testing, CNN (Basic), GridSearchCV, Causal Inference, Feature Engineering
ETL / ELT & Workflow Tools: Apache Airflow, dbt, Jenkins (CI/CD), DataOps, Anomaly Detection, Data Cleansing & Transformation
Tools & IDEs: Jupyter Notebook, VS Code, Git, Jira, PowerPoint, Excel, Tableau Prep, Linux (Ubuntu)
Project Management & Collaboration: Agile/Scrum, Jira, Git (version control), Stakeholder communication, Requirement gathering, Business storytelling
Microsoft Excel (Pivot Tables, VLOOKUP, Macros, VBA scripting for automation)
About
• Results-driven and detail-oriented Data Analyst with 3 years of experience delivering data-driven insights and building scalable solutions across e-commerce, finance, and consulting sectors.
• Proven track record in end-to-end machine learning pipelines—from data collection, feature engineering, model development, and hyperparameter tuning to deployment—on structured, semi-structured, and unstructured datasets using Python, R-Studio, SQL, Power BI, and Azure.
• Expertise includes statistical analysis, A/B testing, predictive modeling, customer segmentation, and churn/retention analytics, with hands-on experience in building growth strategies through data storytelling and engagement optimization.
• Designed interactive Power BI dashboards using Scatter Plots, Maps, Line/Bar/Pie charts to uncover trends, track KPIs, and drive performance improvements.
• Well-versed in pulling and transforming large datasets from cloud platforms like AWS and Azure, applying machine learning models (regression, classification, clustering), and developing strategies for customer retention, revenue growth, and efficiency.
• Strong knowledge of Hadoop ecosystem, Spark, and data engineering pipelines to support large-scale data analytics.
• Recognized for business acumen, marketing intelligence, and the ability to translate complex analytics into actionable solutions.
• Excellent communication, documentation, and time management skills, with a proven ability to collaborate with cross-functional teams and stakeholders in Agile environments.
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