Data Science Team Leader

Salary: £100,000 - 100,000 per year

Requirements:

• A Masters degree or PhD in Data Science, Computer Science, Statistics, or a related quantitative field.
• Proven, extensive experience in leadership and people management, with a demonstrated ability to mentor, guide, and develop Data Scientists.
• Prior hands-on experience developing, deploying, and maintaining machine learning models in a corporate environment.
• Advanced conceptual proficiency in data science and machine learning methodologies, ideally with experience in logistics, geospatial analysis, and ETA prediction or routing problems.
• Experience with deep learning is considered a plus.
• Demonstrated experience in root-cause analysis of complex production model performance issues and the ability to translate those findings into effective business and technical solutions.
• Strong understanding of the model lifecycle and best practices, including testing, code reviews, and monitoring.
• Exceptional communication and stakeholder management skills, with the ability to influence technical peers and non-technical business leaders.

Responsibilities:

• Lead, manage, and scale a high-performing team of Data Scientists through mentorship, coaching, and performance management.
• Foster a collaborative and results-driven team culture.
• Own the teams contribution to defining logistics estimation solutions, ensuring direct alignment with critical company objectives and the broader business strategy.
• Champion data science innovation ideas and partner closely with Product Management to prioritize work based on business opportunities.
• Proactively manage dependencies across the cross-functional team, including continuous collaboration with Machine Learning and Backend Engineers for post-purchase ETA implementation.
• Communicate the teams direction and impact to senior stakeholders.
• Take ownership of key logistics KPIs, particularly overall ETA accuracy across the customer journey.
• Guide the teams focus on the highest-value initiatives and ensure data science moves in a data-driven direction.
• Drive deep analysis to uncover the root causes and underlying business drivers of accuracy gaps in ETA models.
• Diagnose operational friction points such as courier re-assignments and restaurant preparation delays that impact model performance.
• Translate root-cause analysis findings into concrete, actionable plans and conceptual designs for incorporating new features or models.
• Act as the primary interface between the Data Science team and the wider audience, including Product, Operations, and Engineering.
• Translate complex data insights and machine learning concepts into clear, actionable business insights for non-technical audiences.
• Focus on the conceptual design and validation strategy for new predictive features and models.
• Define what the model needs to achieve and how it should be validated.
• Serve as the senior technical expert, guiding architectural decisions for prediction models and maintaining high standards through design discussions and model reviews.
• Partner closely with Machine Learning Engineers to transition robust model designs and thoroughly documented algorithmic logic for production implementation.
• Guide the team in deep-dive analysis of large-scale geospatial and real-time data to translate findings into actionable modeling recommendations.

Technologies:

• Backend
• Machine Learning
• Network
• Product Manager

More:

hackajob is partnering directly with Just Eat Takeaway.com to hire for this role. We are a leading global online food delivery marketplace with a tech ecosystem that connects millions of active customers with hundreds of thousands of connected partners in countries across the globe. Our mission is to empower every food moment around the world, and this role is based in Berlin, London, or Amsterdam, with 3 days in the office and 2 days working from home. You will report to the Data Science Manager and join a fun, fast-paced, supportive culture focused on movement, growth, helping one another succeed, and celebrating wins. We are committed to inclusion, diversity, and belonging, creating an environment where everyone can bring their full selves to work and feel they truly belong.

last updated 34 week of 2026