Data Scientist with 5+ Years in ML, Analytics, and AI Solutions
Resume:
Professional Summary Siva Ranjani Nallagatla
Data Scientist with 5+ years of experience delivering end-to-end machine learning and AI solutions across energy, finance, and healthcare. Specialized in predictive modeling, LLM-powered applications (GPT, RAG), and scalable ML deployment using Python, SQL, and cloud platforms (AWS/Azure). Proven track record of transforming complex data into actionable insights that drive operational efficiency and strategic decision-making.
Technical Skills
Programming & Data Analysis: Python (Pandas, NumPy, Scikit-learn, XGBoost), SQL, SAS, Excel
Data Visualization & BI Tools: Power BI, Tableau, Matplotlib, Seaborn
Machine Learning & Statistics: Regression, Classification, Random Forest, Feature Engineering, EDA, Hypothesis Testing, Predictive Modeling
Data Management & ETL: Data Cleaning, Data Integration, ETL Pipelines, Cloud Platforms (AWS, Azure), Data Validation
Healthcare & Finance Systems: Epic EHR, Cerner, AML/KYC Compliance, Risk Assessment
Other Skills: Dashboard Development, KPI Tracking, Process Automation, Cross-functional Collaboration, Reporting & Presentation
Professional Experience
NiSource Apr 2025 - Present
Data Scientist Atlanta, GA
Developed end-to-end machine learning solutions (Linear Regression, Random Forest, XGBoost) for energy demand forecasting, improving prediction accuracy and enabling data-driven operational planning.
Designed and implemented LLM-powered solutions, including GPT fine-tuning, advanced prompt engineering, and Retrieval-Augmented Generation (RAG) systems using embeddings and vector databases to enhance contextual intelligence.
Performed comprehensive exploratory data analysis (EDA), feature engineering, and statistical hypothesis testing to uncover patterns, optimize model performance, and deliver actionable business insights.
Built scalable ML pipelines using Python, TensorFlow, PyTorch, and Scikit-learn, managing the full lifecycle from data preparation and model training to evaluation and production deployment.
Developed and maintained robust ETL workflows integrating structured and unstructured data from SQL/NoSQL databases and cloud platforms (AWS/Azure), ensuring high-quality, reliable datasets for analytics.
Collaborated with engineering and operations teams to translate complex business requirements into analytical frameworks, driving improvements in forecasting accuracy and process optimization.
Implemented production-grade deployment practices using Airflow for orchestration, Docker and Kubernetes for containerization, CI/CD pipelines, and model monitoring with drift detection, ensuring scalable and reliable AI solutions.
JPMorgan Chase Oct 2024 - Mar 2025
Data Scientist Atlanta, GA
Analyzed large-scale client and transaction datasets using Python, SQL, and Excel to identify trends, detect anomalies, and enhance risk monitoring processes.
Developed predictive models for client risk scoring, fraud detection, and AML alert prioritization, improving accuracy and reducing false positives.
Automated reporting and dashboard creation in Power BI / Tableau, tracking KPIs such as suspicious transactions, high-risk clients, and AML compliance metrics.
Conducted statistical analysis and trend forecasting to support data-driven decisions on client onboarding and regulatory compliance.
Collaborated with cross-functional teams to translate business requirements into scalable data solutions and actionable insights.
Evaluated source of wealth and fund declaration patterns using data analytics techniques to support compliance and business intelligence initiatives.
Designed and implemented Python/SQL scripts to streamline manual compliance processes, reducing operational effort and increasing efficiency by 25%.
JPMorgan Chase Jan 2024 - Oct 2024
Wealth Management Analyst Atlanta, GA
Conducted comprehensive client risk assessments, identifying potential risks such as criminal activities, political affiliations, and suspicious transactions.
Verified client identities and documentation (passports, driver’s licenses, and address proofs) to ensure compliance with KYC and AML regulations.
Executed Customer Due Diligence (CDD) and Enhanced Due Diligence (EDD) processes to evaluate client risk profiles and validate source of wealth (SOW) and fund declarations.
Monitored financial transactions and flagged suspicious activities, ensuring adherence to internal policies and external regulatory requirements.
Maintained accurate client records and periodic reviews, generating daily, weekly, and monthly MI reports using MS Excel and SQL.
Collaborated with regulatory bodies and internal stakeholders to uphold industry standards and implement process improvements.
Contributed to automation initiatives, reducing manual compliance checks by 25% and improving operational efficiency.
Acted as Subject Matter Expert (SME) for the Indian team, providing two months of training on AML procedures, regulatory updates, and bank secrecy act compliance.
Becton Dickinson Jul 2020 - Aug 2022
Healthcare Analyst / Healthcare Data Analyst Chennai, India
Extracted, cleaned, and analyzed large healthcare datasets using SQL and SAS to support clinical, operational, and financial decision-making.
Generated and interpreted reports from Epic and Cerner EHR systems to evaluate patient outcomes and utilization trends.
Developed interactive dashboards in Tableau and Power BI to track KPIs including readmission rates and revenue cycle performance.
Performed data validation and quality assurance processes ensuring HIPAA compliance and data accuracy.
Collaborated with clinical, regulatory, finance, and IT teams to translate business requirements into analytical solutions.
Conducted statistical analysis and trend forecasting to identify inefficiencies and support cost-reduction strategies.
Automated reporting workflows and optimized ETL processes, improving reporting efficiency and reducing manual effort.
CloudTechnologies Dec 2019 - Jun 2020
Intern Data Analyst Hyderabad, India
Analyzed operational and financial datasets using SQL and Excel to identify trends and provide actionable insights to management for business decisions.
Created interactive dashboards in Tableau / Power BI to track key performance indicators (KPIs) such as revenue, customer engagement, and process efficiency.
Generated weekly and monthly reports highlighting business performance, enabling leadership to monitor targets and implement improvements.
Collaborated with cross-functional teams to translate business questions into data-driven solutions and recommend process optimizations.
Supported strategic initiatives by summarizing analytical findings into concise presentations for stakeholders, improving visibility into business performance
Education
Masters in Business Analytics-May 2024
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