Director Data Science

About the Team

The Data Science division acts like the Avengers to the organization's S.H.I.E.L.D, tackling complex problems with innovative data-driven solutions. The team pioneers intelligent systems that serve millions of users navigating thousands of product categories, addressing challenges such as fraud detection, inventory optimization, and language localization on the platform.

Role Overview

This leadership position calls for a strategic mind passionate about harnessing data to solve large-scale business challenges. The Director of Data Science will guide an expert team in designing and deploying machine learning systems that drive significant user impact and business growth. Collaborating across product, technology, and business functions, the role demands ownership of the data science roadmap, converting ambiguity into actionable, scalable solutions.

Responsibilities

• Lead, develop, and mentor a high-performing data science team.
• Take full ownership of data science models and systems within your focus area, from conception through deployment and monitoring.
• Partner with senior leaders across product, engineering, and business to prioritize and define AI/ML initiatives with measurable impact.
• Serve as the Data Science representative in executive-level discussions, articulating technical approaches, investment rationales, and business benefits clearly.
• Influence platform development, system architecture, and enhancements to the machine learning lifecycle.
• Guarantee model scalability, optimize performance and cost-efficiency, and ensure rigorous experimental and statistical standards.
• Guide the team in adopting cutting-edge research and making decisions regarding in-house developments versus third-party solutions.
• Lead root cause analysis for major production incidents, enhancing system monitoring, documentation, and service reliability.

Qualifications and Preferred Experience

• Master’s degree required; PhD in Machine Learning, Statistics, Computer Science, or a similar quantitative discipline is preferred.
• Over 10 years of experience in Data Science or Analytics fields, including a minimum of 6 years managing people.
• Demonstrable research foundation with deep insights into the current state of AI and ML.
• Proven ability to develop and deploy machine learning models at production scale.
• Experience leading large teams (20+ data scientists) and managing cross-functional projects.
• Expertise in ML algorithms, experimental design, and performance evaluation.
• Proficient programming skills in Python and SQL; familiarity with big data tools such as Spark, Hive, or Redshift.
• Capability to convert business challenges into technical solutions, roadmap prioritization, and estimating effort accurately.
• Excellent communication and stakeholder management skills, with a focus on clear execution and prompt action.
• Experience building large-scale AI/ML applications for recommendation engines, ranking, search, or retrieval systems.
• Background in leading ML projects within B2C or e-commerce environments.
• Contributions to internal tools, open source projects, or research papers are advantageous.
• In-depth knowledge of the trade-offs in ML system performance, including latency, cost, and throughput.
• Top-tier publications in AI and ML domains, especially in recommendation systems, information retrieval, and knowledge discovery, are a plus.