Agentic AI
Orchestration, investigation workflows, and systems that reason with evidence.
LangGraph · Vertex AI · LLM-as-JudgeHi, I’m Prateek.
I build AI for
the real world.
A data science leader who still loves to build. I turn complex business problems into machine learning and generative AI products people use.
Senior Data Science ManagerLG Electronics North America
Building on experience at
LG ElectronicsamazonfractalBoston University
- Customers scored daily
- 35M+
- Customer intelligence at LG
- Business KPIs monitored
- 26
- Forecasting and agentic investigation
- Student projects reviewed
- 1,000+
- Mentoring through Udacity
Selected work
Complex problems.
Useful products.
From detecting an unexpected business change to understanding a customer’s next purchase. A closer look at what I build.
Real-time performance monitoring
Forecast
Detect
Investigate
Explain
From a business question to a working system.Workflow overview
LG Electronics
Finding the signal. Explaining the why.
A monitoring and investigation platform that catches business anomalies and turns alerts into evidence-backed explanations.
- business KPIs
- 26
- detection cadence
- 5 min
How I work
The model is
only the beginning.
I care about the full journey: the business question, the engineering, the evaluation, and what happens after launch.
Production ML
Forecasting, customer intelligence, and models connected to real business decisions.
Python · Time series · Gradient boostingGenerative AI
Grounded generation, contextual search, and human review built into the workflow.
RAG · Large language models · NLPThe journey so far
Always learning.
Always building.
From business analytics to leading production AI. Each role has brought me closer to the point where data becomes a decision.
View full résuméAug 2023 — PresentLG ElectronicsSenior Data Science Manager / Lead Data Scientist
New Jersey, United States
Lead the data science team, set technical direction, and personally design, code, and ship production AI systems. Own the work from discovery and modeling through deployment and adoption.
- Real-time forecasting, anomaly detection, and agentic investigation for 26 KPIs.
- Customer intelligence that scores 35M+ customers daily.
- RAG-based campaign creation, LLM personalization, and an internal analytics assistant.
Jun 2022 — Mar 2023AmazonData Scientist
Seattle, United States
Built semantic search for an internal tool serving 38,000+ employees, and developed Python Dash applications to put ML and NLP capabilities in the hands of non-technical users.
- LSI, TF-IDF, SVD, hyperparameter tuning, and ensemble result ranking.
Jun 2019 — Oct 2020Fractal AnalyticsData Science Consultant
Mumbai, India
Worked with General Mills' finance team and Mondelez's global supply chain team on decision-support dashboards, business KPIs, and Python-based data automation.
- Built Tableau dashboards for finance, supply chain, and executive decision-making.
Mar 2019 — Jan 2021UdacityData Science Mentor & Reviewer
Remote
Mentored Business Analytics and Predictive Analytics Nanodegree students through live teaching and individual project reviews.
- Reviewed more than 1,000 student projects.
Oct 2018 — Feb 2019FabHotelsBusiness Intelligence Analyst
Gurugram, India
Worked with the founding team and CMO on booking reliability, fraud detection, and pricing. A customer scoring and confirmation process helped reduce no-show rates from 25% to 13%.
- Built regression models, Python analysis, and tools for cluster managers.
Nov 2017 — Jul 2018OneDirectBusiness Analyst
Bengaluru, India
Analyzed brand performance and marketing campaigns, built analytical reports, and introduced Python web crawlers to improve the team's data collection.
Jul 2017 — Aug 2017SpoylData Analyst Intern
Bengaluru, India
Supported acquisition and marketing teams with campaign analysis, data extraction, and dashboards.
A little about me
Curious by nature.
Hands-on by choice.
I’m happiest at the intersection of a hard problem, a blank editor, and a team that cares about getting it right.
At LG, I lead the data science team and stay close to the code. My work spans classical machine learning, multi-agent systems, and generative AI—with a focus on making them reliable enough for everyday use.
That means thinking beyond model accuracy. It means benchmarking, monitoring, and working with the people who will actually use what we build.
Boston University
Master’s in Applied Data Analytics
2021 – 2022Udacity
Machine Learning, Data Visualization &
Predictive Analytics Nanodegrees
Beyond the day job
Teaching is part
of the work.
I mentor through KaggleX and previously taught and reviewed more than 1,000 student projects at Udacity. I also write about data science, NLP, and machine learning.
Read my writing on MediumLet’s connect
Good things start
with a conversation.
Production ML, agentic workflows, or the gap between AI research and real products—I’m always happy to compare notes.