Charith Nukala
Data Analyst • United States • c*************@gmail.com • +19******678 • linkedin.com/••••• • drivetube.ai/•••••
Professional Summary
Data Analyst with 4+ years of experience delivering enterprise analytics and data-engineering solutions using SQL, Python, Snowflake and Databricks. Experienced across finance and healthcare domains, I design ETL pipelines with Apache Airflow and Spark, build production ML models with scikit-learn/XGBoost, and deliver executive dashboards in Power BI and Tableau. I have implemented cloud data flows on AWS (S3, Lambda, Glue) and GCP BigQuery, enforced data governance for HIPAA-sensitive datasets, and integrated validation into CI/CD to raise data reliability. I own the end-to-end analytics lifecycle—data modeling, performance tuning, forecasting, A/B testing, and stakeholder-facing reporting—helping enterprise teams make faster, evidence-driven decisions against multi-million-dollar budgets and distributed production environments.
Technical Skills
Programming Language: Python,SQL,SAS,VBA
Databases: Snowflake
Cloud Platforms: Amazon Web Services,S3,Lambda,AWS Glue
Version Control & Development Tools: Git
DevOps & Infrastructure: Continuous Integration,Continuous Deployment
Data Engineering & Processing: Apache Airflow,Parquet
Data Analysis & Visualization: Power BI,Tableau,Microsoft Excel,A,B Testing
Machine Learning & AI: SHAP
AI/ML Frameworks & Libraries: scikit-learn,XGBoost
Project Management & Collaboration: Jira
Work Experience
State Farm
Irving, TX
Data Analyst
Oct 2023 – Present
Supported enterprise analytics for State Farm (property & casualty insurance), delivering reporting, forecasting and data-quality improvements for finance and operations.
Tech Stack: Snowflake, Databricks, SQL, Python, AWS S3, Power BI, Tableau, scikit-learn, CI, CD, Jira
- Architected scalable insurance data models in Snowflake and Databricks using advanced SQL (CTEs, window functions, partitioning), improving operational efficiency by 22% across enterprise workflows.
- Automated multi-source reporting workflows using Python (Pandas) and Excel (VBA) integrated with AWS S3 pipelines, cutting manual effort by 12+ hours/week.
- Conducted exploratory analysis and controlled A/B testing with Python and statistical methods to identify operational inefficiencies that produced $200K in annual savings.
- Built executive KPI dashboards in Power BI and Tableau backed by Snowflake views, streamlining ETL data flows to accelerate leadership reporting and decision cycles.
- Developed predictive forecasting models with scikit-learn using engineered features and cross-validation to support business units managing budgets exceeding $5M, improving forecast reliability for planning.
- Optimized complex SQL queries and materialized views in Snowflake and Databricks to improve pipeline throughput and reduce compute consumption.
- Implemented automated data-quality validation and anomaly detection integrated into CI/CD pipelines, raising data integrity across critical reporting systems.
- Led Agile sprint planning and requirements sessions via Jira with product, finance, and operations to prioritize analytics deliverables and ensure on-time releases.
Tata Consultancy Services (TCS)
Hyderabad, India
Data Analyst
Jul 2021 – Aug 2023
Delivered analytics and ETL solutions for healthcare clients, building cloud data pipelines, BI dashboards and statistical analyses to support clinical and operational decisions.
Tech Stack: SQL, BigQuery, Python, Apache Airflow, Spark, Parquet, Power BI, Tableau, Git, SAS, AWS S3
- Transformed large-scale healthcare datasets using advanced SQL across AWS S3 and GCP BigQuery, improving reporting accuracy by 25%.
- Designed interactive BI dashboards in Power BI and Tableau with Parquet-optimized datasets to surface clinical and operational insights that improved care delivery.
- Built automated ETL pipelines using Python, Apache Airflow, and Spark to eliminate manual processing and accelerate data availability for analytics consumers.
- Applied statistical forecasting and cost-analysis models across cloud warehouses, delivering $150K in annual cost reductions for key healthcare operations.
- Optimized SQL reporting logic and standardized Git-based deployments to shorten report production cycles and improve repeatability.
- Executed controlled A/B experiments and hypothesis tests using Python and SAS to evaluate clinical interventions and identify statistically significant impacts.
- Enforced HIPAA-aligned data governance across cloud environments through access controls, audit logging, and data lineage practices to protect patient information.
- Drove Agile/Jira teams with analysts, engineers, and clinical stakeholders to prioritize backlog and improve analytics delivery velocity.
Projects
Customer Churn Prediction & Analytics Platform
Tools Used: Python, SQL, PostgreSQL, AWS S3, AWS Lambda, AWS Glue, Power BI, scikit-learn, XGBoost, SHAP
- Built an end-to-end churn prediction pipeline using Python (XGBoost, scikit-learn) and PostgreSQL, engineering 40+ features from 500K+ customer records to achieve 89% model accuracy and AUC-ROC of 0.93 across cross-validated sets.
- Automated ETL workflows on AWS (S3, Lambda, Glue) to ingest and transform behavioral data on a schedule, reducing pipeline processing time by 40% while ensuring consistent data quality for modeling.
- Designed a real-time Power BI dashboard tracking 12+ KPIs (churn probability, CLV, retention rate) to enable targeted retention strategies and project an expected 17% churn reduction.
- Applied SHAP analysis for model interpretability, quantifying feature contributions and delivering prioritized recommendations to product and customer-success stakeholders.
Education
Cleveland State University
Master of Science in Information Systems • Cleveland, OH
Certifications
Python for Data Analysis (NumPy, Pandas)
Generative AI & Agentic AI Fundamentals
Microsoft Excel & Power BI for Data Analysis and Visualization
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