Data Scientist

'

: - ( - )

Experience: 8+ yrs

Location: Bangalore

As a Data Scientist, you will lead the development of sophisticated price elasticity models that drive strategic pricing decisions across diverse product lines. Leveraging advanced econometric techniques and machine learning algorithms, you will analyze large-scale transactional data, consumer behavior patterns, and market dynamics to quantify price sensitivities and forecast demand shifts. Your insights will directly influence pricing strategies, promotional planning, and revenue optimization initiatives, ensuring that business objectives are met with data-driven precision. In a fast-paced, collaborative environment, you will partner with cross-functional teams to translate analytical findings into actionable business recommendations.

Requirements

• Design, implement, and validate nonlinear and parametric price elasticity models using econometric and machine learning methods.
• Extract, clean, and preprocess large volumes of sales, pricing, and consumer data from multiple sources.
• Conduct hypothesis testing, causal inference, and scenario analysis to evaluate pricing experiments and promotional campaigns.
• Deploy predictive models into production pipelines, ensuring scalability and robustness for real-time pricing decisions.
• Create interactive dashboards and visualizations to communicate model insights to stakeholders.
• Collaborate with product, marketing, and finance teams to align modeling efforts with business strategy.
• Stay abreast of industry trends, emerging techniques, and best practices in price optimization.
• Document modeling workflows, assumptions, and results for audit and reproducibility.
• Mentor junior analysts and provide technical guidance on data science methodologies.
• Continuously monitor model performance, conduct post-deployment reviews, and iterate improvements.
• 8+ years of experience in data science with a strong focus on pricing and demand modeling.
• Proficiency in statistical programming languages such as Python, R, or Julia, and familiarity with SQL and data warehousing concepts.
• Deep knowledge of econometric techniques (e.g., logit, probit, BLP) and machine learning models (e.g., random forest, XGBoost) applied to price elasticity.
• Demonstrated ability to build end-to-end analytical solutions from data ingestion to model deployment.
• Strong analytical mindset with a proven track record of turning complex data into actionable business insights.
• Excellent communication skills for presenting technical findings to non-technical audiences.
• Experience working in a dynamic, cross-functional team environment.
• Familiarity with cloud platforms (AWS, GCP, Azure) and data pipeline tools (Airflow, dbt).
• Ability to navigate ambiguous problems, iterate rapidly, and deliver high-impact solutions.
• Passion for continuous learning and staying current with the latest research in pricing analytics.