Senior / Lead Data Scientist

Quick Facts

• Role: Senior / Lead Data Scientist

Description

You will own end-to-end production ML and GenAI systems, from problem framing and system design through deployment, monitoring, and continuous improvement. The role is hands-on, with responsibility for outcomes and the ability to influence technical direction and engineering practices.

Responsibilities

• Own ML and GenAI systems end-to-end in production: problem framing, system design, deployment, monitoring, and iteration

• Make architectural and methodological decisions for ML systems on AWS, balancing robustness, observability, cost, and maintainability

• Collaborate with Product, Engineering, and Business to turn ambiguous problems into ML-enabled product solutions

• Operate and evolve ML systems across multiple countries and markets, accounting for data distribution differences and regulatory constraints

• Mentor other data scientists through design reviews, technical guidance, and shared ownership

• Raise the bar for engineering practices across the Data Science organization

Requirements

• 5+ years of experience building and owning production ML systems end-to-end in real-world environments

• Advanced degree in Computer Science, Engineering, Mathematics, or comparable field

• Strong hands-on expertise in Python and modern ML frameworks (PyTorch)

• Production experience shipping, operating, and evolving ML systems

• Solid AWS experience (EC2, S3, permissions setup, security services) and MLOps practices (Grafana) including deployment and monitoring at scale

• Expertise with MLflow (knowledge of a 3-base model is a must)

• Practical experience applying GenAI/LLMs in applied or production contexts, including understanding trade-offs and limitations

• Ability to influence technical decisions through judgment and collaboration

• Experience mentoring junior data scientists through hands-on collaboration, code reviews, and technical feedback

• Strong ownership and accountability for outcomes with a pragmatic trade-off and delivery approach

• Excellent verbal and written English

Benefits

• Hands-on role with opportunities to influence technical direction and raise engineering practices across the Data Science organization.