Available to hire
I’m Bindu Pathlavath, an AI/ML Engineer based in Chicago, with 4+ years of experience in machine learning, deep learning, and data analytics. I’m proficient in Python, R, SQL, C++, TensorFlow, PyTorch, Keras, and Scikit-learn, and I enjoy turning complex data into actionable insights.
I’m passionate about building end-to-end ML pipelines, applying Generative AI and LLMs, leveraging cloud platforms, and practicing responsible AI. I thrive in collaborative environments and continuously seek opportunities to optimize models, improve fairness, and deliver measurable business impact.
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Language
English
Fluent
Work Experience
AI/ML Engineer at JPMorgan Chase
December 1, 2024 - PresentDesigned and deployed ML and deep learning models for credit risk, anomaly detection, and fraud prevention. Built scalable ETL and feature engineering pipelines with AWS (S3, Lambda, SageMaker) to automate data ingestion and model training. Implemented MLOps workflows for CI/CD and monitoring, leveraging Docker and Git to speed up production rollout and reproducibility. Improved predictive accuracy by 18% and automation efficiency by 25%. Delivered insights through Power BI dashboards and Python visualizations to enhance portfolio risk detection and KPI tracking.
Data Scientist at Fractal Analytics
April 1, 2021 - July 1, 2023Collected, processed, and analyzed structured and unstructured data using Python, SQL, and PySpark to support ML model development. Developed predictive and classification models for sales forecasting, customer churn, and demand planning, achieving notable accuracy gains. Performed feature engineering, hyperparameter tuning, and model validation, and built automated preprocessing pipelines to improve scalability and reproducibility. Created Power BI and Tableau dashboards to monitor KPIs and accelerate decision-making.
Data Scientist at Fractal Analytics, India
April 1, 2021 - July 1, 2023Collected, processed, and analyzed structured and unstructured data using Python (Pandas, NumPy), SQL, and PySpark. Developed predictive and classification models for sales forecasting, customer churn, and demand planning. Improved model accuracy by 22% and generated actionable business insights using Scikit-learn, TensorFlow, and XGBoost. Performed feature engineering, hyperparameter tuning, and model validation using cross-validation and A/B testing. Created automated preprocessing and transformation pipelines. Built interactive dashboards in Power BI and Tableau to monitor key metrics and KPIs.
AI/ML Engineer at Synechron
April 1, 2021 - July 1, 2023Improved supervised machine learning models (XGBoost, LightGBM, Random Forest) for customer churn prediction, sales optimization, and segmentation, increasing client retention by 15% and improving campaign efficiency. Built computer vision models using CNNs and transfer learning for document classification, invoice processing, and image analytics, reducing manual review and improving throughput by 20%. Systematized feature engineering, hyperparameter tuning, and model evaluation pipelines using Python and Scikit-learn, shortening development cycles while increasing regression and classification accuracy. Deployed end-to-end ML solutions using Flask APIs and cloud platforms (AWS S3, Google Colab), integrating inference pipelines with client applications and delivering real-time insights. Applied responsible AI practices including model interpretability and fairness checks, ensuring bias mitigation and compliance in AI/ML solutions for enterprise clients.
Data Scientist at Fractal Analytics
March 1, 2020 - March 1, 2021Expanded regression and classification models for sales forecasting, demand prediction, and pricing optimization, improving forecast accuracy by 12% for retail and FMCG clients. Performed data analysis using Python, R, and SQL on large structured and unstructured datasets, identifying patterns, trends, and anomalies to support data-driven business decisions. Built interactive dashboards and visualizations in Tableau and Power BI to communicate key predictive insights and performance metrics to stakeholders. Conducted exploratory data analysis, feature engineering, and model evaluation to enhance predictive performance, reduce error rates, and ensure robustness for deployment. Collaborated with business teams to identify AI/ML opportunities and implement responsible data-driven solutions, delivering measurable operational and revenue improvements.
Education
Master of Science in Business Analytics at University of Massachusetts, Boston
January 11, 2030 - May 1, 2025Bachelor of Engineering in Electrical and Electronics Engineering at Vasavi College of Engineering, Hyderabad
January 11, 2030 - June 1, 2023Master of Science in Business Analytics at University of Massachusetts, Boston
January 11, 2030 - May 1, 2025Bachelor of Engineering in Electrical and Electronics Engineering at Vasavi College of Engineering, Hyderabad
January 11, 2030 - June 1, 2023Master of Science in Business Analytics at University of Massachusetts, Boston
January 11, 2030 - May 1, 2025Bachelor of Engineering in Electrical and Electronics Engineering at Vasavi College of Engineering, Hyderabad
January 11, 2030 - June 1, 2023Master of Science in Business Analytics at University of Massachusetts, Boston
January 11, 2030 - May 1, 2025Bachelor of Engineering in Electrical and Electronics Engineering at Vasavi College of Engineering, Hyderabad
January 11, 2030 - June 1, 2023Qualifications
Business Analytics and Data Mining Modeling using R
January 11, 2030 - December 1, 2025Power BI Essential Training
January 11, 2030 - December 1, 2025Business Analytics and Data Mining Modeling using R – NPTEL
January 11, 2030 - January 26, 2026Power BI Essential Training – LinkedIn
January 11, 2030 - January 26, 2026Business Analytics and Data Mining Modeling using R – NPTEL
January 11, 2030 - March 5, 2026Power BI Essential Training — LinkedIn
January 11, 2030 - March 5, 2026Google AI Essentials Specialization – Coursera
January 11, 2030 - March 5, 2026Business Analytics and Data Mining Modeling using R
January 11, 2030 - March 5, 2026Power BI Essential Training (LinkedIn)
January 11, 2030 - March 5, 2026Google AI Essentials Specialization (Coursera)
January 11, 2030 - March 5, 2026Industry Experience
Financial Services, Software & Internet, Professional Services, Other
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