Data Science Team Leader

A global leader in performance marketing, is looking for a talented Data Science Team Leader to join us on our mission to simplify decision-making for millions!

What You'll Do

Responsibilities:

• Lead, coach, and grow an applied data science team; set a high bar for craft, collaboration, and impact.
• Own the full ML lifecycle - from problem framing and experimentation to scalable deployment, monitoring, and continual improvement.
• Build and refine statistical & ML solutions on large-scale data (feature pipelines, metric estimation, insights), translating new research into production where it matters.
• Uphold excellence in MLOps and data: code review and reproducibility, CI/CD for models, explainability and observability, and strong data quality/governance/compliance.
• Collaboration across teams: Work closely with cross-functional teams - product managers, engineers, and business leaders - to identify opportunities, prioritize initiatives, and deliver impactful results.
• Work hands-on with LLM embeddings - selection, evaluation, retrieval pipelines/vector stores - and integrate embedding features into downstream ML models at scale.
• End-to-end project ownership with advanced modeling: Take ownership of projects from ideation and design to deployment, leveraging advanced machine learning and deep learning techniques to develop innovative solutions that address complex business challenges.
• Develop scalable production-ready code: Develop for both real-time and batch modeling pipelines, collaborating with data and engineering teams for seamless integration.
• Innovation and research: Stay ahead of industry trends by exploring and applying cutting-edge advancements in data science, machine learning, and AI to solve emerging challenges.
• Lead the definition and build of products that form our core response to the AI-native “new search” era.

Requirements:

• MSc in a quantitative field (math, statistics, computer science. etc.)
• 3+ years of experience leading ML teams
• Deep statistical & mathematical knowledge (regression, linear algebra, properties of distributions, etc.) and the ability to understand, utilize and innovate on state-of-the art machine learning algorithms and statistical modeling
• Strong background in Python with experience in Data & ML packages and OOP
• Developing production systems
• Experience with AWS ecosystems - an advantage