Manager Data Science

Overview

As Manager, Data Science, you lead a team delivering intelligent, data-driven systems that help users explore and act on complex information. You set strategy, balance delivery with long-term technical investments, and guide production-ready AI solutions that blend retrieval, ranking, and generation. You work with engineering and product partners to raise the technical bar and align priorities with business goals. This role combines strong ML foundations with practical, scalable AI approaches in a collaborative, responsible framework.

Pay / Benefits

• wellbeing initiatives
• shared parental leave
• study assistance
• sabbaticals
• flexible working hours
• competitive compensation (location-specific)

Responsibilities

• Lead and develop a team of data scientists, shaping growth, performance, and careers
• Set team strategy and operating rhythms aligned with product goals
• Manage capacity across initiatives, balancing short-term delivery with long-term investment
• Establish inclusive culture grounded in scientific rigor, collaboration, customer focus, and responsible AI
• Define best practices for experimentation, evaluation, data quality, production collaboration, and documentation
• Recruit and retain top data science talent
• Guide end-to-end ML/AI system delivery from problem framing to deployment and iteration
• Oversee systems that combine retrieval, ranking, and generation to support intelligent workflows
• Balance model performance with product, reliability, scalability, and cost considerations
• Partner with engineering to ensure production-ready, secure, and maintainable solutions
• Review technical approaches and unblock teams while maintaining hands-on depth
• Define evaluation strategies for models, retrieval, and product features
• Promote responsible AI practices including transparency, bias assessment, and risk management
• Communicate progress, risks, and trade-offs to technical and non-technical audiences
• Represent data science in cross-functional planning and contribute to broader AI strategy

Key requirements

• Extensive experience in data science or related field
• Experience directly managing or leading data scientists or technical professionals
• Proven track record delivering production-quality AI solutions through a team
• Strong understanding of ML fundamentals, experimentation, and model evaluation
• Strong Python skills and ability to review production-grade systems
• Experience with large, complex, unstructured datasets
• Ability to manage multiple priorities and make sound trade-offs
• Strong stakeholder-management and communication skills
• Experience with large language models in applied/production settings
• Experience with retrieval approaches, embeddings, semantic search, and ranking
• Experience guiding LLM-powered systems with multi-step reasoning and workflow orchestration
• Ability to choose appropriate classical ML, retrieval, or LLM approaches
• Experience designing evaluation frameworks for AI outputs
• Familiarity with ML frameworks (PyTorch, TensorFlow, Scikit-learn, Hugging Face)
• Experience with cloud platforms, Git, CI/CD, and MLOps practices
• Experience collaborating with engineering on scalable system design
• Familiarity with vector databases or search infrastructure (Elasticsearch, OpenSearch, Qdrant)

• Strong communication with both technical and non-technical audiences
• Collaborative leadership and people development
• Strategic thinking and stakeholder management
• PyTorch
• TensorFlow
• Scikit-learn

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