Senior Director, Data Science

About the role:

• 
  Strategic Leadership:
• • Lead and develop the Data Science and ML Engineering teams to deliver actionable business insights and production-grade ML solutions.
  • Collaborate with senior leadership to define the analytics and AI roadmap aligned to retail business priorities (pricing, promotions, assortment, personalized marketing, and customer experience).
• Team Management and Mentoring:
• • Build, mentor, and retain a high-performing team of data scientists and machine learning engineers.
  • Foster a culture of innovation, continuous learning, and excellence.
• Solution Design and Delivery:
• • Oversee end-to-end delivery of advanced analytics and machine learning projects, from ideation to deployment and ongoing optimization.
  • Architect and implement scalable models for price optimization, promotion effectiveness, assortment planning, demand forecasting, and personalized marketing.
• Hands-on Technical Oversight:
• • Guide the team in leveraging modern data science tools and frameworks (Python, R, Spark).
  • Champion the adoption and integration of GenAI (Generative AI) for real-world retail applications (e.g., automated content creation, chatbot solutions, recommendation systems).
• Deployment & Integration:
• • Drive best practices for robust model deployment and MLOps, ensuring seamless integration of models into retail software platforms or products.
  • Work closely with product and engineering teams to operationalize data science solutions at scale.

About you:

• 10+ years of industry experience in data science and machine learning; min 3+ years in a leadership role managing data science and/or ML engineering teams.
• Demonstrated expertise in retail analytics (price optimization, promotion analytics, assortment planning, personalization, customer segmentation, etc.).
• Advanced degree (PhD/Masters) in Computer Science, Statistics, Mathematics, Data Science, or related field.
• Extensive hands-on experience in Python (scikit-learn, pandas, TensorFlow/PyTorch), R, and Spark.
• Proven experience with designing, building, and deploying production-grade ML models and integrating with existing business software/systems.
• Strong understanding of MLOps, Cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes) is highly desirable.
• Experience with GenAI frameworks, applications, and responsible AI principles.

• Competitive salary and benefits package.
• Opportunities to work on innovative, cutting-edge technology projects.
• Supportive, collaborative, and technically enriching work environment.
• Professional growth and upskilling opportunities.