Data Science Lead

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.

Description Hebrew

Data Science Lead – Optimization & Advanced Analytics

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.