---
title: "Drishpreet Singh - Lead Data Scientist in Bengaluru | Tal"
description: "Meet Drishpreet Singh, Leading AI-ML & Operations Research Initiatives based in Bengaluru. AI stack includes claude code, codex, and hugging face."
image: "https://tal.club/meet/drishpreet-singh/share-image"
---

# Drishpreet Singh on Tal

## Headline

Leading AI\-ML & Operations Research Initiatives

## About

Experienced in Data Analysis, Data Science and Business Analysis while partnering with wide spectrum of industries including second largest Search Engine Marketing firm, Oil and Gas company, Food and Beverages company and second largest retail network of USA\. Worked on data driven approaches to generate the valuable insights for decision making and solving complex business problems\.

## Location

Bengaluru

## AI stack

claude code

codex

hugging face

langchain

langgraph

Google ADK

## Work experience

Lead Data Scientist at Anko GCC, Feb 2026 \- Present · 7 mos, Team Leadership & Portfolio Ownership — Lead a team of 4–6 data scientists across the optimization and agentic AI portfolio, setting technical direction, running solver design and code reviews, and mentoring on OR formulation and LLM system design\. Own the annual roadmap jointly with Supply Chain, Trade Compliance and Merchandising leadership, from problem framing through production deployment\. Container Unpack Scheduling & Selection — Built a lexicographic multi\-objective optimization engine in Google OR\-Tools that selects and sequences containers for daily unpack\. Demurrage, lost sales, putaway capacity, DC congestion and demand coverage are solved in strict priority order, each tier's optimum frozen as a constraint before the next is optimized\. Served via FastAPI behind a React planning interface; delivered \~5M AUD in annual savings\. Multi\-Agent HS Code, Tariff & Statistical Code Classification — Architected a multimodal multi\-agent system assigning HS codes, duty and tariff rates and statistical codes for products imported into the Australian and New Zealand markets, with agents for product text and image attribute extraction, tariff document retrieval, GRI\-based narrowing and confidence\-scored adjudication\. Avoids \~4M AUD of penalty exposure and releases \~900 hours of manual effort per month\.

Senior Data Scientist at Anko GCC, Sep 2023 \- Feb 2026 · 2 yrs 6 mos, Greater Bengaluru Area, Container Packing Optimization — Built and deployed a multi\-objective MILP generating container loading plans daily across 300 port pairs, balancing cube and weight utilisation against carton compatibility and downstream unpack effort, and streamlining the unpacking process at destination DCs\. Delivered a net impact of \~3M AUD in EBIT savings and became the standing planning process for inbound freight\. Option Flow Modelling — Deployed an optimization engine coupled with a predictive model to design the most efficient cycle times for SKUs across the season, determining how long each option stays on floor before markdown so that full\-price sell\-through is maximised without stranding inventory at end of life\. Rolled out across categories and embedded into the seasonal range planning cycle\. ANA\-CHAT Conversational Analytics Bot — Built the first agentic workflow at ANKO for an end\-to\-end conversational analytics bot, translating business questions into query plans, running causal analysis on the results and returning narrated charts, with tool\-use orchestration, guardrails and evaluation for production use\. Adopted by business teams for self\-serve analysis previously routed through the data team\.

Data Scientist at Victoria’s Secret & Co\., May 2022 \- Sep 2023 · 1 yr 5 mos, Price Optimization & Elasticity Modeling — Built a non\-linear log\-log LOWESS and curve\-fit model estimating price elasticity by item type, quantifying how demand responds to discount depth across categories and price bands\. Productionised it as the analytical basis for setting campaign discount ladders, replacing judgement\-led discounting with elasticity\-informed depth across the brand portfolio and giving merchants a defensible basis for markdown depth\. Boosted Consumer Model — Built an XGBoost propensity model powering CRM strategy for the VS mega\-brand and its sub\-brands, engineering behavioural and transactional features to score customers for campaign targeting and contact strategy across channels\. Delivered an increment of \~2M in net sales over the prior rules\-based segmentation approach, and became the standard scoring layer for campaign planning\. Competitor Value Strategy — Quantified the impact of mall store closures against competitor presence and catchment overlap, leveraging the Four\-Square REST API for location and footfall signals to build a comparative view of each trade area\. Informed which markets warranted fleet investment versus consolidation as the store estate was rationalised, and shaped the closure shortlist presented to leadership\.

Senior Analyst S&OP at Target, Nov 2021 \- May 2022 · 7 mos, India

Senior Supply Chain Analyst at Target, Jun 2020 \- May 2022 · 2 yrs, Package Volume Forecasting — Built a multi\-variable linear regression model predicting the count and type of packages leaving Sortation Centers for last\-mile digital fulfilment, validated against actuals at 90% accuracy\. Gave network operations a reliable daily forward view for labour staffing, sort plan design and carrier capacity commitments ahead of each fulfilment week\. Recursive Node Max Optimization — Designed a recursion algorithm to allocate overflowed demand across fulfilment nodes when a node reached capacity, cascading residual volume to the next best node under cost and service constraints\. Improved resource planning and inventory allocation across the digital network during peak and high\-volume events, where manual reallocation had previously been the fallback\. Order Simulation & Real\-Time Re\-projection — Simulated digital demand orders on stratified samples to derive demand allocation by fulfilment type, and built a VBA\-Python tool re\-projecting event\-day digital performance every hour so operations could intervene intra\-day\. Also owned hourly business intelligence reporting for digital performance across the network, giving leaders a same\-day view of trading\.

Analyst S&OP at Target, Jun 2020 \- Nov 2021 · 1 yr 6 mos, Bengaluru, Karnataka, India

Data Scientist at Mu Sigma Inc\., Sep 2018 \- Jun 2020 · 1 yr 10 mos, Tight Rock Sequence Builder — Designed a sequencing tool for a drilling team using genetic algorithm minimisation on a heavily constrained problem, ordering drilling operations under rig availability, geology and scheduling constraints\. Reduced non\-productive time between wells and gave planners a repeatable way to evaluate alternative sequences before committing rig time\. Social Media Sentiment Analysis — Implemented NLP and text mining over social conversation data to devise a consumer rating for a new chips flavour in the APAC region, building the cleaning, tokenisation and lexicon\-scoring pipeline end to end\. Gave the brand team an early read on reception ahead of a wider regional rollout, and a reusable pipeline the team applied to later product launches\.

Trainee Decision Scientist at Mu Sigma Inc\., Aug 2018 \- Jun 2020 · 1 yr 11 mos, Bangalore

Intern Operations Excellence at Hindustan Coca\-Cola Beverages Pvt Ltd, May 2017 \- Jul 2017 · 3 mos, Bengaluru, Karnataka, India

## Education

Postgraduate Degree, Data Science, International Institute of Information Technology Bangalore

Bachelor of Engineering \- BE, Industrial Engineering, Dr\. B R Ambedkar National Institute of Technology, Jalandhar \( PUNJAB\)

[View the original profile](https://tal.club/meet/drishpreet-singh)

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