Data Analyst Machine Learning

VEERABADHRA SAI PREETHAM VOLETI

Data Analyst

Chicago, IL *************@*****.*** +1 (312) 625- 2398 LinkedIn PROFESSIONAL SUMMARY:

Over 4+ years of experience in advanced Data Analyst with a proven track record in healthcare and finance, adept at transforming complex data into actionable insights. Expertise spans ETL (Talend, Apache Airflow, SSIS, AWS Glue, Google BigQuery), data cleaning (Python Pandas, SQL, Excel) and advanced analytics. Proficient in developing and deploying machine learning and deep learning models (Scikit-learn, PyTorch, TensorFlow) for predictive modeling, classification, clustering and time-series forecasting. Skilled in data visualization and dashboarding (Tableau, Power BI, Seaborn, Matplotlib, ggplot2) and statistical analysis (A/B testing, T-tests, Chi- square, ANOVA). Experienced in optimizing relational databases (MySQL, PostgreSQL, Teradata, Amazon Redshift), designing data warehouses (Snowflake, Azure Synapse) and leveraging real-time processing (Apache Kafka, Spark, Databricks), while ensuring strict data governance and compliance with HIPAA, HL7, ICD, AML, KYC and Basel III.

TECHNICAL SKILLS:

Data Analysis & Visualization: Python (Pandas, Matplotlib, Seaborn, Scikit-learn), Power BI, Tableau, Google Optimize, Excel (VBA Macros, Advanced Functions) Programming Languages: R, Python

ETL & Data Processing: Talend, Apache Airflow, AWS Glue, Google BigQuery, Snowflake, Teradata, Azure Synapse Analytics, SQL Server Integration Services

(SSIS)

Machine Learning & Statistical Analysis: Scikit-learn, TensorFlow, PyTorch, Regression Modeling, Classification (KNN, Decision Trees, Naive Bayes, Random Forest, SVM, Gradient Boosting), Time-Series Forecasting, Predictive Analytics, Deep Learning, A/B Testing, Hypothesis Testing (T-tests, Chi-square, ANOVA)

Database Management: MySQL, PostgreSQL, Amazon Redshift, Teradata, Snowflake, SQL

(Query Optimization, Complex Queries)

Data Governance & Compliance: HIPAA, ICD, HL7, KYC, AML, Basel III, Data Governance Protocols Project Management & Collaboration: Agile, Scrum, Jira, Trello, Confluence, Git, SVN GitHub Data Warehousing: Snowflake, Teradata, Amazon Redshift, Azure Synapse Analytics, OLAP

Cloud Platforms: AWS (Redshift, Glue), Azure Synapse,Hadoop Statistical Tools & Methods: Python (Statistical Analysis), A/B Testing, Regression Analysis, Scenario Simulations, Root cause analysis, Probability Distributions Other Skills: Databricks, DBT, Kafka, Spark, Predictive Modelling, Linear Algebra, advanced analytics, Data Mining, Data Profiling, Data Reporting, Data warehousing, Data Transformation,Data Cleaning, Data Wrangling, Data Architecture, Database Building,

Operating System: Mac OS, Windows, Linux

PROFESSIONAL EXPERIENCE:

GE HealthCare – IL May 2024 - Present

Data Analyst

• Extract, transform and load (ETL) healthcare data from various sources using tools such as Talend, Apache Airflow, SSIS, AWS Glue and Google BigQuery.

• Clean, preprocess and validate large datasets using Python (Pandas), SQL and Excel to ensure accuracy, completeness and consistency.

• Crafted and optimized complex SQL queries across MySQL, PostgreSQL, Teradata, and Amazon Redshift to extract patient data, generate clinical performance reports, and ensure audit compliance in line with HIPAA and HL7 standards.

• Participate in designing scalable data warehouse solutions using Snowflake, Azure Synapse and OLAP/OLTP structures for healthcare reporting and analytics

• Collaborated with cross-functional teams (clinicians, business analysts, compliance officers) to define KPIs, design data models, and drive analytics strategy aligned with care delivery and compliance objectives.

• Develop dashboards and interactive visualizations using Tableau and Seaborn to communicate key healthcare KPIs to stakeholders by 15%.

• Perform A/B testing and statistical hypothesis testing (T-tests, Chi-square, ANOVA) to support decisions in care delivery improvements and digital health interventions

• Applied linear, logistic and exponential regression models to forecast treatment success rates and medication adherence trends across time, resulting in a 14% increase in preventive care intervention planning accuracy.

• Implemented unsupervised learning techniques including K-Means & Hierarchical Clustering for patient segmentation based on medical history, demographics & treatment adherence using Scikit-learn & visualized clusters using ggplot2.

• Designed and deployed deep learning models using PyTorch and TensorFlow to predict patient readmission risk, achieving a 17% improvement in model accuracy over traditional logistic regression approaches.

• Ensure strict compliance with data privacy and regulatory standards such as HIPAA, HL7, ICD, AML and data governance protocols while handling sensitive healthcare data. Accenture – India July 2020 to July 2023

Data Analyst

• Collect, clean and transform financial and transactional data using Talend, Apache Airflow, SSIS, AWS Glue and Google BigQuery to ensure data accuracy and compliance with Basel III requirements by 20%.

• Analyze customer behavior, credit performance and transaction patterns using Python (Pandas, Seaborn, Matplotlib), Excel (VBA Macros, advanced functions) and SQL for business insights and reporting (20%).

• Collaborated with stakeholders across credit risk, finance, compliance, and product teams to define analytical KPIs and translate regulatory and business requirements into actionable insights.

• Build financial dashboard & KPI reports using Power BI to support strategic decisions across risk, finance teams.

• Conduct A/B testing and statistical hypothesis testing (T-tests, ANOVA, Chi-square) to optimize marketing campaigns, loan offers and user experience strategies

• Wrote and optimized advanced SQL queries on MySQL, PostgreSQL, Redshift, and Teradata to support financial reporting, credit risk modeling, and Basel III audit readiness.

• Utilized ggplot2 in R to create data visualizations for financial forecasting and portfolio analysis, enabling clear communication of complex trends to finance and risk management teams.

• Utilize Apache Kafka, Spark and Databricks for real-time data processing and transformation in high-volume financial environments by 10%.

• Supported model validation and analytics for credit scoring and fraud detection in collaboration with data science teams, contributing to a 15% increase in prediction accuracy.

• Applied advanced classification algorithms (Decision Trees, KNN, Naive Bayes, Random Forest) & clustering techniques using Scikit-learn to segment customers & identify high-risk transaction patterns, enhancing fraud detection process.

• Built and validated logistic regression and gradient boosting models to predict loan default probabilities, integrating results into Tableau dashboards for real-time monitoring by credit analysts.

• Ensured strict compliance with data privacy and regulatory frameworks such as AML, KYC, GDPR, and data governance protocols while managing sensitive customer and transaction data. EDUCATION:

MASTER OF SCIENCE IN INFORMATION TECHNOLOGY AND MANAGEMENT, DATA ANALYTICS – Illinois Institute of Technology, Chicago, Illinois BACHELOR OF SCIENCE IN ELECTRONICS AND COMMUNICATION ENGINEERING - SRM Institute of Science and Technology, Chennai, India CERTIFICATIONS:

• CERTIFIED SNOWPRO CORE– Snowflake

• CERTIFIED MICROSOFT AZURE AI ENGINEER ASSOCIATE - Microsoft

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