Data Science Lead- R&D and Innovation Center

Description 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. As a Data Science Lead, 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: Develop complex optimization models using 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, utilizing 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. Requirements PhD in Mathematics, Operations Research, Computer Science, or a related quantitative discipline (Master’s degree also considered). 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. Proven ability to translate business problems into mathematical models and implement 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. Full time Job Location: Tel Aviv, Hybrid We at Deloitte believe that diversity and inclusion among our people is a critical component of our success and that is why we cultivate an organizational culture that contains and embraces diversity in all its forms. Requirements Hebrew 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.