Gen AI & Data Science Engineer Resume Title

480-***-**** *****.**********@*****.***** com linkedin.Mahajan com/in/amrit-mahajan lightning-nemesis.github.io EDUCATION

Arizona State University Tempe, Arizona

Master of Science in Computer Science GPA: 4.0/4.0 Aug. 2024 - May 2026

● Relevant Coursework - Statistical Machine Learning, Data Mining, Natural Language Processing, Artificial Intelligence, Data-intensive systems for ML, Data Visualization, Cloud Computing, Data Processing at Scale Vellore Institute of Technology, Vellore Vellore, India Bachelor’s in Computer Science GPA: 9.29/10 Merit Scholarship Recipient (Top 10 rank)Jul. 2018 - May 2022 WORK EXPERIENCE

Wells Fargo Charlotte, NC

Quantitative Analytics Intern, Gen AI team June 2025 - Aug. 2025

● Built a POC Generative AI Question Answering system using customer data, providing bankers with accurate context-aware insights and reducing client preparation time by ~30% in pilot testing.

● Designed an LLM evaluation framework using DeepEval and DSPy, implementing HITL, LLM-as-a-judge, and adversarial testing to benchmark model reliability, alignment, and safety across projects.

● Tested a hybrid RAG pipeline (BM25 + FAISS) that reduced retrieval latency by ~85% by replacing long-context large-model prompting with targeted chunk retrieval and smaller models. Bajaj Finance Limited Pune, India

Data Scientist Jul. 2022 - Jul. 2024

● Led development and deployment of ML-based Customer Churn Prediction model on the Bajaj Finserv App

(40M+ users), driving a 3.8% retention lift through targeted strategies.

● Built a Notification Recommendation Engine on clickstream data that boosted CTR by 25%, reducing manual campaign effort to zero across 40 business teams while improving leads, journey completions, and conversions.

● Pioneered MLOps adoption by implementing MLflow in Databricks, cutting manual deployment effort by 50%, standardizing A/B testing, and enabling adoption by 3+ teams. Bajaj Finance Limited Pune, India

Data Science Intern Jan. 2022 - Jul. 2022

● Automated forecasting pipelines using Pandas and PySpark, cutting monthly reporting time for app metrics

(MAU, DAU, traffic, and net users) from 5–6 days in Excel to 1 day.

● Analyzed notification and app uninstallation patterns with tree-based interpretable models, guiding informed governance changes that mitigated churn and reduced notifications costs. SKILLS

Programming: Python, SQL, PySpark, C++, NumPy, Pandas AI/ML: Statistics, Predictive Modeling, Time Series, Deep Learning, NLP, LLMs, RAG, MLOps Frameworks & Tools: Scikit-learn, TensorFlow, Databricks, MLflow, LangChain, Power BI, Excel, Git, Flask ACADEMIC PROJECTS

Identifying LLM Performance Gaps Across Languages Research Project at ASU

● Evaluated multilingual performance gaps in LLMs using OLMo models across 100+ languages and 5 reasoning domains (Math, Reasoning, NLI, Common sense, healthcare) using high-quality translation pipelines.

● Quantified correlation between structural factors (language-token exposure, parallel data, script effects) in pre-training/post-training data and cross-lingual accuracy to guide fairer LLM development. ClickLess AI: Autonomous Grocery Shopping Agent

● Built a conversational AI agent that converts natural language into checkout-ready grocery carts using Instacart API, Knowledge Graphs, and LLM orchestration with automated checkout via BrowserUse and Playwright.

● Integrated Open Food Facts for dietary constraint satisfaction, with privacy-preserving on-device inference. LEADERSHIP, AWARDS AND EXTRACURRICULAR

Dale Carnegie Program on Training Excellence - Strengthened communication, storytelling, & leadership Mar. 2024 Certified Trainer, Bajaj Finance - Delivered technical training sessions to 60+ employees Mar. 2024 Runner-up, Visual AI Hackathon by Voxel51 - Built Hazard Zone Monitoring system using YOLOv8 Feb. 2025 HEROES Award, Bajaj Finance - Exceptional performance Jan. 2023 Finalist, Code For Good hackathon by JP Morgan Chase & Co.Jun. 2022

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