מוביל דאטה סיינס IIH

Role Overview Deloitte’s R&D Center in Israel is seeking an exceptional Data Science Lead with a PhD in Mathematics, Operations Research, Computer Science, or a related quantitative field. This role is ideal for candidates with a proven track record in formulating and solving complex numerical optimization problems, particularly in mixed integer programming (MIP), linear programming (LP), and related domains. You will play a pivotal role in driving innovation for our product and retail optimization teams, overseeing advanced analytics projects, and mentoring junior data scientists. Key Responsibilities Strategic Leadership • Oversee Data Science Initiatives: Lead the data science team’s workstreams, ensuring alignment with business objectives and technical excellence. • Execution Leadership: Direct optimization-focused teams, guiding solution design and delivery for asset, product, and placement optimization projects (e.g., planogram optimization, assortment and allocation optimization, whitespace/category optimization). Technical Excellence • Problem Formulation: Collaborate with stakeholders to translate business challenges into mathematical optimization problems. • Solver Implementation: Express complex optimization models in solver constraint languages (Gurobi, Pyomo, etc.), ensuring robust, scalable, and maintainable code. • Python Development: Build and maintain backend code integrating optimization solvers, leveraging Python for data manipulation, model orchestration, and automation. • Framework Expertise: Apply best practices in numerical optimization, leveraging industry-standard frameworks and libraries. Innovation & Thought Leadership • Recommender Systems: Contribute to the design and implementation of recommender systems and other advanced analytics solutions as needed. • Research & Development: Stay abreast of emerging trends in optimization, machine learning, and retail analytics, and champion their adoption within the team. Collaboration & Mentorship • Team Development: Mentor junior data scientists, fostering a culture of continuous learning and technical rigor. • Cross-Functional Collaboration: Work closely with product managers, engineers, and business stakeholders to deliver impactful solutions. Required Qualifications • PhD in Mathematics, Operations Research, Computer Science, or a related quantitative discipline (Masters degree are possible as well). • Deep expertise in formulating and solving numerical optimization problems (MIP, LP, etc.). • Hands-on experience with optimization frameworks such as Gurobi, Pyomo, CPLEX, or similar. • Proficiency in Python for backend integration and model development. • Track record of translating business problems into mathematical models and implementing end-to-end optimization solutions. • Excellent communication and stakeholder management skills. Preferred Qualifications • Experience in retail analytics: planogram optimization, assortment optimization, allocation optimization, whitespace/category optimization. • Familiarity with recommender systems and related machine learning techniques. • Prior leadership experience in data science or optimization teams. • Experience working in a global, cross-functional environment.