AI/Data Scientist

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Nandan Keshav Hegde

********@***.*** GitHub Portfolio Rarepeti Academic and Professional references Experience certificates Mobile: +1-517-***-**** Education

Michigan State University

Sep 2024 – April 2026 (Expected) MI, USA

Master of Science in Computational Data Science (STEM Designated) GPA: 3.9/4.0 (Top 1% of Class) GRE 321/340 Manipal University, Manipal Institute of Technology Jun 2015 – Nov 2019 Manipal, India

Bachelor of Technology in Electrical and Electronics Engineering GPA: 8.1/10.0 (Top 10% of Class) Internship

Emergence.ai

AI Research intern May 2025 – Present NYC, New York, USA (remote)

• ACA Benchmarking: Built experiment suite to evaluate the Agent Creating Agent (ACA) framework for autonomous tool generation and orchestration, delivering effective root cause analysis to streamline development and ship enhancements faster

• Gen Agent (CRAFT Evaluation): Part of the Data and Research team to improve the Gen Agent for CRAFT (Emergence AI's flagship enterprise automation platform), gaining critical insights on repeatability, consistency, and tool creation capabilities via LLM as judge benchmarking, improving agent performance and reliability by at least 10%

• Data Semantic Ablation studies: Designed an experimental suite to evaluate how Generative Foundational models handle Text2SQL tasks through varying proportions of noise and accurate knowledge base context, with a goal to achieve SOTA performance on existing benchmarks Ramsi.ai (Formerly PricingService.ai)

Data Science Research intern Sep 2025 – Present Boulder, Colorado, USA (remote)

• Design and implementation of Pricing solutions: Built and deployed non parametric explainable models for price prediction and causal inference using 2 Stage Residual Integrations for premium and Boutique Hotel tiers, improving prediction power and expanding research scope by 2x.

• Foundational Dynamic Pricing model: Niche groundwork and exploration to build novel foundational models aimed at being able to generalize on in house pricing datasets to eventually build SOTA Foundational Dynamic Pricing models Work Experience

Tredence Analytics Solutions Private Limited

Data Science Consultant Jun 2023 – Jul 2024 Bengaluru, India

• Promo Optimization & Pricing Simulator (Domain: Retail): Designed data driven framework to simulate pricing and promotional impacts across key SKUs, identifying optimal promo combinations for pilot implementation, aligning promotional strategies with business uplift goals and revenue targets.

• Promo Effectiveness Analysis (Domain: Retail): Developed baseline and lift modelling for promotional events, leading to ~20–25% decrease in inefficient spending and improving ROI benchmarks across targeted campaigns, enabling data driven promotional budget allocation.

• Product/Item Matching (Domain: Retail): Built NLP pipeline to automate SKU alignment across vendors and platforms, improving match accuracy to 65% and saving ~250–300 hours annually in manual reconciliation efforts, streamlining cross platform inventory management. Incedo Technology Solutions Limited

Senior Data Scientist Feb 2021 – May 2023 Bengaluru, India

• Demand Forecasting (Domain: CPG): Created ML models to improve forecast precision by ~10%, enabling better supply chain alignment and reducing excess inventory costs, with estimated annual savings of $200K–$300K through optimized demand planning and inventory management.

• Enterprise Data Service Workbench (Domain: Financial Service): Led development of a self service analytics platform for RFP support, increasing proposal throughput by ~40–50% and reducing average turnaround time, enabling faster client response cycles and improved win rates.

• Client Cohort Analysis (Domain: Financial Service): Delivered behavioural segmentation for investor profiling, aiding in targeted engagement strategies that led to ~10% lift in RFP conversion rates and ~20% quarterly revenue growth through personalized client outreach and retention strategies.

• Investment Director Performance Dashboard (Domain: Financial Service): Developed retrospective portfolio insights dashboard tracking KPIs across advisory/discretionary channels, improving transparency and decision support for directors through interactive visualizations and performance benchmarking. ZS Associates India Private Limited

Decision Analytics Associate Jan 2020 – Jan 2021 Pune, India

• Survival Analysis (Domain: Pharma and HealthCare): Applied time to event modelling to predict therapy switch patterns, contributing to ~15–20% reduction in patient churn and improving client engagement strategy through early intervention targeting and retention modeling.

• New Patient Adoption Modelling (Domain: Pharma and HealthCare): Built ML models to rank HCPs by likelihood of prescribing new therapies, leading to improved sales force effectiveness and ~25–30% reduction in targeting costs through optimized territory alignment and call planning.

• Marketing Mix Modelling (Domain: Pharma and HealthCare): Streamlined regression based MMM processes, reducing model delivery cycles by 30–40% and identifying high ROI promotional levers, contributing to ~10–15% marketing ROI lift through optimized channel allocation and spend efficiency. Research Professional Skill Development

• Advancing Causal Video Question Answering: Fine tuned Generative Foundational Language and Vision models (GFMs) for ensemble approach to multi modal video/text analysis.

• Michigan Farm to Institute (MFIN): Conducted data driven analyses generating actionable insights to foster institutional adoption of locally sourced food systems.

• Foundational Degree in Data Science and Programming, IIT Madras: First cohort to complete an innovative online degree covering Data Science, ML and Programming.

• Certified Cloud Practitioner & Machine Learning (Speciality), AWS: Enrolled in certification programs to enhance Cloud and ML skillsets Skills

• Programming languages and scripting: Python, R Programming, Awk, Bash, SQL, MATLAB

• Machine Learning and AI: Statistical Modelling, Time Series Analysis, Demand Forecasting, PyTorch, TensorFlow, NLP, Computer Vision

• Deep Learning: CNNs, RNNs, Transformers, Attention Mechanisms, Seq2Seq, Diffusion Models, Generative Modelling

• Cloud & Deployment: Azure, AWS, GCP, PySpark, FastAPI, Flask, Streamlit, Vercel, Docker

• Analytics & Platforms: GIT, Advanced Excel, Tableau, Big Query, Database Management Systems

• Agentic AI frameworks & workflows: LiteLLM, MCP (Model Context Protocol), LangChain, RAG, Autonomous task orchestration, Agent Benchmarking Coursework

Deep Learning (CSE 849) Large Language Models (CSE 895) Computer Vision (CSE 847) Machine Learning (CSE 847) MLOps (STT 890) Data Mining (CSE 881) Computational Optimization (CMSE 831) Computational AI (CSE 840) Algorithms & Data Structures (CSE 830) Applied Data Science (CMSE 830) Statistics (STT 810, 811) Recent Capstone Projects

• Agentic review suite: Multi agent AI platform with autonomous peer review, real time research intelligence, streaming orchestration, FastAPI backend and Streamlit dashboard.

• math viz agent: Multi agent math visualisation system that converts natural language to interactive Desmos graphs using Wolfram Alpha computation.

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