Data Scientist Retail Domain

Experience : 6 - 10 Years

Location : Yelahanka, Bangalore

Work Mode : Work from Client Location / On-site

Notice Period : ONLY Immediate Joiners Preferred

About the Role :

We are looking for an experienced Data Scientist with strong expertise in Machine Learning, Python, Demand & Price Optimization, and Time Series Forecasting to join our team.

The ideal candidate must have strong Retail Domain experience and should be able to translate complex business problems into scalable data science solutions. The role will involve working on demand forecasting, pricing optimization, predictive analytics, and AI/ML use cases, along with emerging Generative AI and Agentic AI applications.

The candidate will work closely with business stakeholders, data engineers, product teams, and technology teams to develop and deploy data-driven solutions that deliver measurable business impact.

Key Responsibilities :

- Develop and implement advanced Machine Learning and statistical models for retail business problems.

- Build robust demand forecasting and sales forecasting models using historical and external data.

- Work on price optimization, promotional optimization, markdown optimization, and pricing strategies.

- Develop and enhance Time Series Forecasting models for demand, sales, inventory, pricing, and other retail KPIs.

- Identify business opportunities where AI/ML can improve revenue, profitability, customer experience, and operational efficiency.

- Perform exploratory data analysis, feature engineering, model development, validation, and performance optimization.

- Design experiments and evaluate different algorithms and modeling approaches.

- Work with large and complex datasets to identify patterns, trends, anomalies, and actionable insights.

- Develop scalable and production-ready Python-based ML solutions.

- Apply Generative AI and Large Language Models (LLMs) to relevant business use cases.

- Explore and implement Agentic AI solutions and AI-driven workflows.

- Collaborate with data engineers to ensure data availability, quality, transformation, and pipeline readiness.

- Communicate analytical findings and model outcomes effectively to both technical and non-technical stakeholders.

- Monitor model performance and continuously improve models based on business requirements and changing data patterns.

Must-Have Skills :

- Machine Learning & Data Science : Strong hands-on experience in Machine Learning, supervised/unsupervised learning, feature engineering, and model validation.

- Python : Strong expertise in Python with libraries like Pandas, NumPy, and Scikit-learn.

- Demand & Price Optimization : Strong experience in Demand Forecasting, Price Optimization, and retail analytics.

- Time Series Forecasting : Strong hands-on experience with forecasting methodologies, seasonality, and trends.

- GenAI & Agentic AI : Practical exposure to LLMs, RAG, and Agentic AI frameworks.

Retail Domain Mandatory :

- Retail Domain experience is a MUST. Candidates should have experience working on one or more of the following retail use cases: Demand/Sales Forecasting, Price/Promotion/Markdown/Inventory/Assortment Optimization, Customer/Product Analytics, or Revenue/Margin Optimization.

Education :

- Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative discipline.