Senior Manager of Data Science/Machine Learning

Role overview

Join CookUnity as a Senior Manager of Data Science / Machine Learning to drive product innovation with advanced data science capabilities. You will lead a team building predictive modeling and personalization solutions, and use data-driven insights to shape the product roadmap.

Key missions

• Define and execute the product data science strategy, identifying opportunities where machine learning and predictive analytics can deliver meaningful improvements in customer experience and business results.
• Build and lead a data science/ML team focused on:
  • Predictive modeling and personalization
  • Experimentation frameworks
  • Emerging ML capabilities impacting customer engagement, retention, and customer lifetime value
• Act as a thought leader on emerging data science techniques—e.g., personalization, recommendation systems, causal inference, and generative AI—and guide their application to product problems.
• Foster a culture of innovation and continuous learning within the data science organization.

Responsibilities

• Translate high-impact opportunities into data science initiatives with strong product sense and business acumen.
• Lead the development and production deployment of ML models, especially for personalization, recommendation systems, and predictive modeling.
• Communicate complex technical concepts to non-technical stakeholders and influence product strategy.

Requirements

• Strong product sense and business acumen.
• Hands-on technical expertise in Python, SQL, and modern ML frameworks: scikit-learn, PyTorch, TensorFlow.
• Experience in consumer tech, e-commerce, or marketplace businesses where personalization and engagement matter.
• Excellent communication skills with non-technical stakeholders.
• Cloud-based data infrastructure experience: AWS, GCP, Snowflake.
• ML Ops tools: MLflow, Airflow, Kubeflow.
• Deep expertise in experimentation and causal inference, including:
  • A/B testing
  • Incrementality measurement
  • Statistical rigor
• 8+ years in data science, including 3+ years in leadership roles managing data scientists or ML engineers.
• Proven track record deploying ML models in production (personalization/recommendations/predictive modeling).
• PhD or Master’s in Computer Science, Statistics, Mathematics, or a related quantitative field.
• Experience with real-time ML systems and feature stores.
• Familiarity with generative AI / LLM applications in product contexts.
• Background in recommendation systems, including two-tower / multi-modal embeddings.
• Experience building teams from scratch or during rapid growth.

Nice to have

• Experience in subscription businesses or retention-focused products.
• Knowledge of product analytics tools: Amplitude, Mixpanel, Looker.