Looking for a job

Srinivasa Supreeth Yenisetty

@srinivasasupreethyen

I'm a data scientist building explainable machine learning products for forecasting, risk assessment, and business decisions.

India

Message

What I'm looking for

I'm looking to build reliable, explainable machine learning and analytics products that turn large real-world datasets into data-driven business decisions.

At Nexturn, I'm building production-facing machine learning solutions from an 8.5M+ record Chicago crime dataset, turning it into crime forecasting and insurance underwriting use cases.

I developed a Streamlit crime intelligence platform spanning dashboards, hotspot analysis, forecasting, and SHAP explanations across 22 police districts and 302 patrol beats. My best XGBoost forecasting model achieved 93.37% classification accuracy, and I containerized the application with Docker for reproducible deployment.

I've also built a CrimeScore underwriting engine for 77 Chicago community areas, achieving R² of 0.92 in validation and 0.87 on an independent test set. I enjoy translating complex data into reliable, interpretable analytics through Python, SQL, feature engineering, visualization, and end-to-end data pipelines.

Experience

Work history, roles, and key accomplishments

Current

Data Science Intern

Current

Nexturn

Feb 2026 - Present (8 months)

Developed end-to-end machine learning solutions for crime forecasting and insurance underwriting using a large Chicago crime dataset. Built and deployed interactive applications with SHAP explainability and containerized deployment.

Python Pandas NumPy scikit learn XGBoost Random Forest LightGBM CatBoost Feature Engineering Model Validation SHAP Streamlit Docker EDA Data Pipelines SQL Power BI Tableau Matplotlib

Education

Degrees, certifications, and relevant coursework

Chaitanya Bharathi Institute of Technology

Bachelor of Engineering, Computer Science Engineering (AI & ML)

Pursuing a Bachelor of Engineering in Computer Science Engineering with a specialization in Artificial Intelligence and Machine Learning, expected to graduate in July 2026.