Full Stack Developer- R&D and Innovation Center

We are seeking a talented Fullstack Developer with backend orientation. The ideal candidate will have professional experience programming in Python and a solid understanding of AI protocols and standards.

In this role you will:

• Analyze complex problems, identify and define the computational requirements to solve them. 
• Utilize your expertise in Python to architect scalable and efficient solutions.
• Utilize GenAI engineering tools such as LangChain, RAG, Vector Database for implementation and optimization.
• Stay updated with AI protocols and standards and ensure their correct application in projects.
• Collaborate with other team members to understand requirements and develop solutions, conduct code reviews, ensure code quality, and enforce best practices.

• 5+ years of professional experience as a Software Developer, with a focus on Python development.
• Experience with React and frontend development.
• Demonstrated experience or strong interest in working with Large Models (LLMs) and RAG such as GPT, etc.
• Knowledge of Backend Frameworks such as and Django.
• Experience with cloud technologies (e.g., AWS, Azure, GCP) and using Docker and Kubernetes.
• Experience working on global teams collaborating via tools such as Jira, Teams, ADO.
• Excellent problem-solving and analytical skills.
• Degree in Computer Science or a related field.
• Advanced level of English. 

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.