Mar 2024 – Aug 2024 · 5 mos · Chicago, Illinois, United States

• Built time series forecasting models for crop factors using an ensemble of statistical, ML, and deep learning frameworks for different forecasting horizons(quarterly, monthly and 8-day averaged) at the county level, employing a hierarchical forecasting approach, to help clients predict Corn and Soybean yields

Jan 2023 – Jun 2023 · 5 mos · Bengaluru, Karnataka, India

• 1. Worked on deep diving into significant revenue loss from Phantom Inventory for a US Retail Store using advanced data analysis on ~Mn SKU-Location records
• 2. Applied a strategic logic framework and Dask for K-means clustering to identify high Ghost areas with potential for a targeted revenue recovery
• 3. Ensured version control and traceability via Vertex AI and GCP BigQuery for reproducibility and scalability

Jun 2021 – Jan 2023 · 1 yr 7 mos · Bengaluru, Karnataka, India

• 1. Worked on Hidden Markov models, for Mid-market teams, contributing to a revenue surge
• 2. Worked on advanced association rule learning algorithms, contributing to quarterly growth in ARPA
• 3. Integrated GA4 and GCP Big Query for dynamic web traffic monitoring

Apr 2020 – Jun 2021 · 1 yr 2 mos · Bengaluru, Karnataka

• 1. Worked on creating a dynamic sales forecasting model with the Prophet algorithm, actively contributing to the formulation of semi-annual goals.
• 2. Collaborated closely on strategic planning and automated data processing, resulting in a significant time-saving and improved report turnaround.

Oct 2018 – Apr 2020 · 1 yr 6 mos · Bengaluru, Karnataka, India

• 1. Contributed to quarterly increase in customer enrollment for new gaming services at a leading US Cable Operator in FY-2019 using K-means clustering and an XGBoost Classifier
• 2. Collaborated in setting up a scalable data architecture for a US-based ISP client, reducing anomalous data with a streamlined Data quality management(DQM)framework
• 3. Worked on sentiment analysis for US-based Wireless Telecom care agents through vectorization and SVM classification, impacting CSAT and NPS improvements

May 2017 – Jul 2017 · 2 mos · Pune, Maharashtra, India

• Achieved a cost reduction in freight operations for the Procurement Team by implementing an integrated Data Envelopment Analysis (DEA) and Analytical Hierarchy Process (AHP) framework, effectively assigning priority and efficiency scores to vendors during the evaluation process.