Utsav Mishra
Lead Data Scientist with 8+ years of experience building machine learning, reinforcement learning, and GenAI systems, including patented solutions delivering over $500M in business impact at Target.
Lead Data Scientist
About Me
I’m a Lead Data Scientist focused on production ML, RL, and GenAI—turning research into systems that hold up at scale (recommendation, personalization, forecasting, and experimentation).
As Lead Data Scientist (L6) at Target, I lead data science for offer personalization: roadmaps and architecture for large platforms, strong MLOps and experimentation practices, and mentorship across a broad team. That work includes patented RL-based personalization (CORE) and newer GenAI/RAG initiatives with clear business metrics.
Outside of work, I like long walks, treks, travel, and music.
Professional Focus
- Technical leadership: ML strategy, experimentation design, and production architecture across cross-functional teams.
- Research to production: End-to-end ownership from modeling choices to deployment and monitoring; CORE delivered major redemption/opt-in uplifts and >$500M in incremental sales.
- People: Mentorship, leveling frameworks, and reusable ML patterns that raise the bar org-wide.
Key Expertise Areas
- Reinforcement Learning: Multi-armed bandits, contextual bandits, DDQN, exploration-exploitation strategies
- Generative AI: RAG-based retrieval systems, LLM integration, automated ML workflows
- Deep Learning: LSTM, CNN, neural architectures, transfer learning
- ML Infrastructure: GCP, VertexAI, Kubeflow, PySpark, TensorFlow, MLOps pipelines
- Causal ML & Experimentation: A/B testing frameworks, causal inference, statistical validation
Academic background
B.Arch (Honours) from Indian Institute of Technology Kharagpur. Coursework included programming and data structures, probability, image processing and remote sensing, and economics. Hackathons and quantitative projects included placements at the Microsoft Azure Hackathon and MishMash Hackathon.
Work Experience
Lead Data Scientist (L6), Target Corporation
October 2021 —
• Architected and owned the ML strategy and technical roadmap for Target's offer personalization platform (100M+ users), defining experimentation frameworks, model architectures, and scaling patterns for multi-market deployment.
• Drove technical architecture decisions across a team of 16 data scientists and engineers, establishing best practices for model design, MLOps pipelines, and cross-team ML integration.
• Mentored and grew 5 data science team members, coaching on advanced ML techniques and research-to-production translation; two received promotions.
• Invented & patented Target's Contextual Offer Recommendation Engine (CORE), an RL-based contextual bandit framework. Architected the system from research to production, driving +70% redemption and +28% opt-in uplift (stat-sig), contributing over $500M incremental sales.
• Designed and led development of TargetRun, a guest-level trip forecasting system using LSTM that achieved statistically significant improvements, reducing MAPE and MAE by ~50% and driving measurable lifts in campaign opt-in, completion, and redemption rates across all engagement segments.
• Designed and led development of Lookalike, a GenAI-powered RAG system that automates campaign forecasting through intelligent retrieval and ranking, achieving 100% coverage (K=3 recommendations), eliminating manual campaign triage.
• Architected automated ML data and training pipelines on GCP using Spark, Kubeflow, and Oozie with TensorFlow Agents; established standardized model tracking and monitoring through TensorBoard and Grafana.
• Technical thought leadership: Presented advanced ML methodologies at company-wide technical forums and received VP Award for Innovation & Impact.
Applied Data Scientist 2, Tata AIA Life
April 2020 — October 2021
• Applied NLP techniques including Gensim LDA topic modeling to identify drop-off points in customer onboarding, achieving 6.2% conversion rate increase. Developed interactive journey visualizations using Plotly Sankey diagrams.
• Developed a GBM regression profit prediction model (R² = 0.991) and deployed it in production via FastAPI; reduced valuation TAT by 30 days. Implemented SHAP for feature attribution and built Streamlit visualization for explainable AI.
Machine Learning Engineer, HDFC Life
January 2018 — March 2020
• Developed a Face Recognition system with Anti-Spoofing capabilities using CNN and DeepFace embeddings to reduce fraud in virtual customer onboarding. Deployed as a containerized service using Docker and ECS.
• Designed and developed the serverless architecture of Lead allocation and Route optimisation app on AWS Data Lake (Lambda, DMS, Dynamodb, Step Function, S3, API Gateway, and Docker).
• Built a cost-sensitive Medical Risk classification model using Deep Reinforcement Learning (DDQN), achieving >91% accuracy while intelligently balancing diagnostic test costs.
Education
Indian Institute of Technology, Kharagpur
B.Arch Honours, ARP
July 2014 — April 2019
Relevant Coursework : Programming & Data Structures, Probability - Mathematics 1 & 2, Image Processing & Remote Sensing, Economics Micro & Macro.
Extracurricular : Sponsorship Head Spring Fest, Web Head SSAP ARP, Lead National Service Scheme Unit - 5.
Recipient of Merit Cum Means Scholarship provided by the Government of India for Academic excellence.
Kendriya Vidyalaya, Andrews Ganj
Science PCM C++
April 2010 — April 2013
Percentage : 88.7% in XII (AIISCE).
Cum GPA : 9.8 in X (AISSE-CBSE)
Received Merit Certificate from CBSE for prolific academic performance in AISSE &AISSCE in 2011 & 2013.
Portfolio
