Data Scientist

Blackstraw Technologies; Chengalpattu; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

Blackstraw Technologies in Chennai is seeking an experienced Data Scientist/ML Lead to design and deploy machine learning models for retail analytics and marketing effectiveness. You will build pricing and promotion models, optimize assortment, and drive data-driven business decisions across pricing, merchandising, and category management.

The role requires 5+ years in data science or advanced analytics, with strong Python/SQL skills, proficiency in causal inference, and experience in

Qualifications

• 5+ years of experience in Data Science, ML, or Advanced Analytics.
• Strong proficiency in Python, SQL, statistics, and ML algorithms.
• Hands-on experience in model development, validation, deployment, and monitoring.
• Experience in incrementality measurement and A/B testing.
• Experience in pricing and promotion analytics.
• Experience in assortment optimization and demand modelling.
• Strong understanding of causal inference and business impact.

Responsibilities

• Develop and deploy ML models for retail analytics and marketing effectiveness.
• Measure campaign incrementality using A/B testing, matched-market testing, MTA, MMM.
• Build pricing and promotion effectiveness models to measure ROI.
• Develop assortment optimization and cross-product demand models.
• Create scalable ML pipelines and productionize models with data engineering.
• Translate insights into actionable recommendations for marketing, pricing, merchandising, and category management.

Skills

Python

SQL

Statistics

Machine Learning

A/B Testing

Causal Inference

Experimentation

Retail Analytics

Job description

Location: Chennai

Notice Period: Immediate Joiners preferred

Role & responsibilities

• Develop and deploy machine learning models for retail analytics, marketing effectiveness, pricing, promotions, and assortment optimization.
• Retail Media Measurement: Measure campaign incrementality and effectiveness using A/B testing, matched-market testing, Multi-Touch Attribution (MTA), and Marketing Mix Modeling (MMM).
• Retail Pricing & Promotions: Build pricing and promotion effectiveness models to measure sales lift, price elasticity, cannibalization, halo effects, and campaign/offer ROI.
• Retail Assortment: Develop assortment optimization, demand transfer, product substitution, and cross-product demand models.
• Apply statistical modelling, causal inference, experimentation, and predictive analytics to measure incremental sales, revenue, and profitability.
• Build scalable ML pipelines and productionize models in collaboration with data engineering and business teams.
• Translate analytical insights into actionable recommendations for marketing, pricing, merchandising, and category management.

Preferred candidate profile

• 5+ years of experience in Data Science, Machine Learning, or Advanced Analytics, preferably in retail, e-commerce, CPG, or retail media.
• Strong proficiency in Python, SQL, statistics, and machine learning algorithms.
• Hands-on experience in model development, validation, deployment, and monitoring.
• Experience in incrementality measurement, A/B testing, matched-market testing, and exposure to MTA/MMM.
• Experience in pricing and promotion analytics, including lift, cannibalization, halo effects, and ROI.
• Experience in assortment optimization, demand transfer, or product substitution modelling.
• Strong understanding of causal inference, experimental design, and business impact measurement.