Lead Data Scientist - Python/SQL (3-6 yrs)

Job Summary :

We are seeking a highly skilled and experienced Lead Data Scientist with a passion for leveraging data to drive impactful business decisions, particularly within the realm of pricing and promotion optimization. You will lead the research, design, and development of advanced statistical and machine learning models to address complex pricing and promotion challenges.

This role requires a deep understanding of data science principles, strong analytical skills, and the ability to translate business problems into actionable data-driven solutions. Experience in the retail industry is highly preferred.

Key Responsibilities :

- Stakeholder Collaboration : Work closely with stakeholders across the organization (i.e., marketing, sales, pricing teams) to understand business needs, identify opportunities for data-driven solutions, and translate these into concrete data science projects.

- Research & Development : Research, design, and develop cutting-edge statistical and machine learning approaches tailored to pricing and promotion optimization problems.

- Stay up-to-date with the latest advancements in data science and apply them to real-world scenarios.

- Project Leadership : Lead end-to-end price optimization and promotion effectiveness projects, from problem definition and data collection to model development, deployment, and evaluation.

- Price Elasticity Modeling : Develop sophisticated price elasticity models to understand the relationship between price and demand.

- Analyze competitive price positioning and recommend optimal pricing strategies.

- Experiment Design & Analysis : Design and analyze A/B/multivariate experiments to test the impact of price changes and promotional offers. Provide statistically sound recommendations based on experiment results.

- Promotional Response Modeling : Build promotional response models to predict lift, cannibalization effects, and other key metrics related to promotional campaigns.

- Markdown Optimization : Develop markdown optimization strategies for seasonal and clearance items to maximize revenue and minimize inventory holding costs.

- Promotional Performance Analysis : Analyze historical promotion performance to identify trends, patterns, and opportunities for improvement. Provide data-driven insights and recommendations for future campaigns.

- Promotional Mix Modeling : Design promotional mix models to optimize campaign spending across different channels and tactics.

- Model Deployment & Maintenance : Build production-ready end-to-end analytics frameworks. Collaborate with engineering teams to deploy models and ensure ongoing monitoring and maintenance.

Required Technical Skills :

- Programming Languages : Expert-level proficiency in Python and SQL.

- Big Data Technologies : Intermediate-level proficiency in PySpark and Databricks.

- Project Management Tools : Beginner/Intermediate-level proficiency in JIRA or similar project management tools.

Preferred Skills :

- Data Visualization : Knowledge of any data visualization tool (i.e. Tableau, Power BI, Matplotlib, Seaborn).

- Cloud Computing : Understanding of cloud infrastructure and architecture (AWS, Azure, GCP).

- Model Monitoring & Maintenance : Knowledge of model monitoring and maintenance techniques.

- Web Frameworks : Experience with Python-based web frameworks (Streamlit, Flask, Dash, Django).

Required Experience & Qualifications :

- Education : Bachelor's or Master's degree in Engineering, Business Analytics, Data Science, Statistics, Economics, Mathematics, or a related field.

- Experience : 3+ years of experience in data science and consulting (Retail industry preferred).

- Problem-Solving Skills : Ability to understand complex business problems and translate them into actionable data science solutions.

- Domain Expertise : Familiarity with pricing and promotion optimization frameworks and best practices.

- Communication Skills : Excellent communication and presentation skills, with the ability to clearly articulate complex technical concepts to both technical and non-technical

- Strong analytical and problem-solving skills.

- Detail-oriented and results-oriented.

- Proactive and self-motivated.

- Passion for data and its potential to drive business value