Data Scientist

Job Description

TITLE: Data Scientist

DEPARTMENT: Data Sciences & Analytics

LOCATION: Bangalore, India

Team:

Data Sciences & Analytics is a global CoE team, incubated within Victoria’ Secret & Co. (VS&Co), building the best-in-class suite of Data Science & Analytics Products that power the best shopping experience for our customers, and deliver actionable, customer-centric insights to our ecommerce, marketing, merchandising and supply chain teams enabling better business decisions on omni channel (digital + store) 360 performances.

Purpose:

The data scientist will play a technical role in architecting data science solutions working with senior team members & business stakeholders to deliver outstanding business outcomes for problems across VS&Co:

•You will be leading the build of machine learning models on:

1.Customer models - segmentations, lookalike, affinity, CLV & propensity models,

2.Agentic AI & GenAI Conversational Assistants,

3.Price elasticity, offer personalization & promo optimization models,

4.Recommendation & personalization systems,

5.Forecasting & optimization systems.

•You have a deep interest and passion for technology. You love writing and owning codes and enjoy working with people who will keep challenging you at every stage. You have strong problem solving, analytic, decision-making, and excellent communication with interpersonal skills. You are self-driven and motivated with the desire to work in a fast-paced, results-driven agile environment with varied responsibilities.

•You will work directly on the AI problems that have the most impact on VS&Co‘s digital e-commerce, customer/marketing, pricing/promotions, forecasting/optimizations.

Responsibilities:

Deliver data science CoE projects from India; Engage & collaborate with business & technology partners. Communicate progress to all stakeholders.

Design the development of solutions that leverage data sciences & advanced analytics to develop required business solutions.

Perform deep exploratory analysis on large scale customer data, identify shopping & interaction patterns, discover price elasticity & price sensitivity behaviors and build lifecycle models for targeting customers towards loyalty.

Build conversational agents to deliver faster insights that drive customer strategy on acquisition, retention & growth.

Evaluate, recommend, & implement state-of-the art algorithms and methods.

Knowledge of MLOps practices.

Education:

B.S. degree in Computer Science, Mathematics, Statistics

M.S. or PH.D. in Computer Science, applied mathematics, statistics, physics, operations research, quantitative social sciences or related fields will be preferred.

Skills/Experiece:

3+ years after Bachelors of relevant experience in data scientist & analytics role preferably in retail domain.

Strong programming skills. Expert level proficiency in Python, SQL.

Strong written & verbal communication skills. Ability to communicate complicated statistical analytical concepts & solutions to business stakeholders in a simplified comprehensible manner.

Excellent presentation skills & ability to shape course of action through persuasion & negotiations.

Collaborate actively with topic owners to understand and develop advanced analytics / data science

Experience designing algorithms for a relevance system such as a personalized tool, search/ranking, recommendations, forecasting, marketing, loyalty, etc.

Strong engineering mindset and exposure to software engineering principles, Agile methodologies, distributed systems and applied Machine Learning.

Experience building Agentic AI systems and hands-on exposure to LLMs, prompt engineering, LLM evaluation frameworks and end-to-end Agentic AI production expertise.

Mandatory Skills:

Machine Learning, Python, Big Data Skills, R, Statistics

Solid experience working with state-of-the-art supervised and unsupervised machine learning algorithms on real-world problems, preferably in ecommerce and retail domains.

Strong ability to understand the business and good stakeholder management capabilities and has mentored data scientists in developing ML solutions.

Experience playing the role of full-stack data scientist and taking solutions to production.