The Opportunity

This role is not a typical data scientist position. We seek an intellectually curious scientist to solve critical marketing problems via quantitative modeling and optimization. You will design, develop, and deploy advanced models influencing personalization, media allocation, and in-store strategy. If you thrive applying rigorous scientific methods to large-scale marketing challenges, this role is for you.

Key Responsibilities

• Architect Recommendation Engines: Design and optimize next-gen personalization models to boost engagement and sales.
• Optimize In-Store Space & Assortment: Use advanced analytics and operations research to maximize profitability per square meter across thousands of stores.
• Lead Media & Marketing Optimization: Build Media Mix Models (MMM) and multi-touch attribution frameworks to measure ROI and optimize marketing spend.
• Drive Quantitative Insights: Define quantitative problems from business questions, leveraging statistics, machine learning, and causal inference for actionable marketing insights.
• Innovate and Research: Stay updated with academic/industry advances in quantitative marketing and machine learning, pioneering their applications here.

Required Qualifications & Skills

• Education: M.S. or Ph.D. in Industrial Engineering, Operations Research, Statistics, Computer Science, Economics, or related fields.
• Experience: 5+ years as a Data Scientist with a proven track record in building and deploying impactful ML models.
• Technical Skills:
• Expert programming in Python (Pandas, NumPy, Scikit-learn) and strong SQL skills.
• Experience with ML frameworks like PyTorch or TensorFlow.
• Hands-on with big data tech such as Spark or Hadoop.
• Marketing Acumen: Solid understanding of marketing and ability to link complex models with business outcomes.
• Problem-Solving: Strong first-principles thinker capable of breaking down unstructured problems into solvable parts.

Preferred Qualifications

• Graduate from top-tier Iranian or international university.
• Experience in retail, CPG, or e-commerce sectors.
• Deep knowledge of optimization techniques (linear/non-linear programming).
• Experience with Graph Neural Networks (GNN) for recommendations.

What We Offer

• Highly competitive salary and benefits.
• Work on strategic, high-impact projects with measurable outcomes.
• Access to industry-unique, massive datasets.
• Culture of intellectual curiosity, continuous learning, and data-driven excellence.
• Clear career progression into technical leadership or management.
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