Data Science Team Lead

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.

• 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.

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.