Data Science Team Leader

This is an exceptional, hands-on, player/coach opportunity to establish, shape, and lead our Data Science capability in the United States. As the Data Science Team Leader, you will be a critical part of our expanding global data organization.
You will remain deeply technical and actively involved in writing code, building models, and executing machine learning solutions, while simultaneously mentoring and growing a high-performing team of US-based Data Scientists and Machine Learning Engineers.
We are intentionally recruiting for a specific kind of professional: someone with a startup mindset who thrives in fast-paced environments, possesses a strong bias for action, and values execution over theoretical complexity. To succeed, you must be a pragmatic problem solver who enjoys getting their hands dirty while building scalable, production-grade solutions.
Excellent stakeholder management is paramount. You will work as a key collaborative partner alongside the US Data Team Lead, Data Product Lead, and AgentOps Team Lead within the wider US Data team, while maintaining strong operational alignment and knowledge sharing with our established UK-based Data Science team.
The listed salary for this position is $155,000 - $165,000 annually.
Proven experience working in a fast-paced, agile, or startup-like environment. You must have a demonstrated passion for “getting things done” and delivering value iteratively.
Prior experience mentoring, coaching, or leading data scientists or engineers while remaining active in code development.
A strong track record of designing, building, deploying, and maintaining machine learning models in production environments
Superior communication skills with the ability to build strong cross-functional relationships and translate technical concepts into business outcomes for both technical and non-technical audiences.
Exceptional programming skills in Python and deep expertise in data science libraries (Scikit-learn, Pandas, NumPy, XGBoost, etc.).
Advanced SQL proficiency for querying and manipulating large datasets, preferably within Google BigQuery.
Hands-on experience with Google Cloud Platform (GCP), ideally including the Vertex AI ecosystem (Pipelines, Workbench, Endpoints).
MSc or PhD in a quantitative discipline (Computer Science, Statistics, Mathematics, Engineering) or equivalent practical industry experience.
Familiarity with containerization (Docker, Kubernetes) and CI/CD principles for machine learning.
Experience with real-time stream processing or event-driven architectures (e.g., Kafka).

Employment type
Full-time

Work arrangement
Hybrid