Data Science Team Lead/Manager

hackajob is collaborating with Bet365 to connect them with exceptional professionals for this role.

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.

Main Responsibilities

In this hands-on role you will devise, code, and deploy AI, machine learning and predictive

models, leading by example in technical execution and code quality. This is not a pure

people-management role.

Building, mentoring, and guiding a pragmatic, delivery-focused team of Junior Data

Scientists and Machine Learning Engineers, fostering a culture of rapid iteration,

continuous learning, and software engineering discipline.

Partnering closely with the Data Team Lead, Data Product Lead, and AgentOps Team Lead

to align data science initiatives with product roadmaps and platform capabilities.

Collaborating regularly with our UK-based Data Science team of technical excellence to

share methodology, align on standards, and leverage global technical capabilities.

Translating complex, ambiguous business questions into clear data science initiatives,

delivering measurable business value through rapid prototyping and deployment cycles.

Collaborating with Machine Learning Engineers to champion the adoption of

robust MLOps practices on our Google Cloud Platform (GCP) stack, ensuring models are

automated, monitored, and scalable.

Establishing data science workflows, standards, and code repositories from scratch in a

new regional office.

The skills and experience to help you perform in the role:

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).