Data Science Manager

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About Zilch

Zilch is a payment tech company on a mission to create the most empowering way to pay for anything, anywhere. Combining the best of debit, credit and savings, we give our customers the option to earn instant cashback or spread the cost of pricier purchases, completely interest free and with no late fees.

About the Role

We are looking for an exceptional Data Science Manager to lead and grow our data science capability, driving the development, deployment, and optimisation of machine‑learning solutions that support Zilch’s mission to deliver responsible, real‑time and seamless credit experiences. This is a leadership role that involves line management of experienced data scientists, while staying hands‑on technically.

Role Responsibilities

• Lead a high‑performing Data Science team that ships and owns predictive models in production, focused on payments products, fraud detection, risk modelling, customer analytics, and product optimisation.
• Work with Product, Risk, Engineering, Operations, and commercial stakeholders to translate business goals into modelling strategies that improve customer outcomes.
• Coach Data Scientists to become more effective and take on new responsibilities, fostering career growth and technical excellence.
• Ensure Data Science work aligns with company objectives via a visible, prioritised model backlog with problem statements, baselines and clear business owners.
• Maintain delivery pace while balancing technical debt, business priorities, and innovation.
• Implement robust value measurement of key business outcomes to guide product strategy and investment decisions.
• Oversee version control, CI/CD integration, and automated model lifecycle management.
• Promote a data‑driven approach to product development, operational decisions, and customer experience improvements.
• Continuously improve tools, processes, and ways of working with code review standards, experiment tracking, model cards/docs, and reproducible pipelines for the data team and cross‑functional stakeholders.
• Work with Product, Risk, Engineering, Operations, and commercial stakeholders to define high‑impact modelling priorities, and partner with engineering to deliver and operate production‑grade ML systems across model serving, feature pipelines, monitoring, drift detection, experimentation, retraining, and A/B or champion‑challenger tests.
• Drive improvements to our MLOps approaches to embed production SLOs/SLIs, monitoring and drift, retraining and roll back, and post‑launch value verification.

What We\’re Looking For

• Manages through clear objectives and context rather than task‑based instructions.
• Strong track record of delivering measurable value in previous roles.
• Significant experience as an individual contributor data scientist shipping models to production, writing high‑quality code, and partnering with engineers on serving & monitoring.
• Able to hold technical conversations at parity with engineers and data scientists.
• Knowledgeable about AI/ML safety, bias detection, and privacy considerations (PII handling and compliance).
• Comfortable delivering small, testable increments to production fast, then iterating based on measured outcomes.
• Champions simplicity and high code quality.
• Strong knowledge of experimental design, A/B testing, and causal inference.
• Keeps technical skills sharp while leading a team.
• Skilled at “telescoping”, seeing the big picture, then diving into critical areas of focus.
• Quickly identifies the root cause when problem‑solving.
• Thrives in a fast‑changing, high‑growth environment.
• Embed responsible AI practices through fairness monitoring, transparent model documentation, and alignment with FCA expectations for explainability and data usage.
• Shape and maintain the modelling roadmap, ensuring prioritisation aligns with product, risk, and commercial outcomes.

Technical Skills

• Proven strong MLOps practice, including CI/CD, cloud‑native model training and deployment, model serving, and effective data lifecycle management.
• Expert proficiency in Python, SQL, and core ML libraries (e.g., Pandas, NumPy, Scikit‑Learn, XGBoost).
• Strong experience working with cloud‑based ML platforms (AWS preferred, e.g., SageMaker).
• Familiarity with model management and deployment tooling such as Git, MLflow, or CI/CD frameworks.

Ways of Working

• Clear and concise communicator, able to translate technical concepts for senior leadership and non‑technical audiences.
• Outcome‑oriented, comfortable working in a fast‑paced and evolving fintech environment.
• Passionate about scalable solutions, high‑quality modelling, and responsible AI principles.
• Leads through empowerment and clarity, while setting a high bar for technical and delivery excellence.

Bonus Skills

• Experience with modern data stack tools (DBT, Snowflake, Looker).
• Exposure to deep learning, LLMs, or advanced ML techniques relevant to fintech.
• Experience developing near‑real‑time scoring pipelines or streaming‑based ML systems.
• Interest in emerging technologies (LLMs, reinforcement learning, real‑time ML, vector search, etc.) and their application in fintech.

Benefits

• Pension scheme.
• Death in Service scheme.
• Income Protection.
• Permanent employees enjoy access to our Share Options Scheme.
• 5% back on in‑app purchases.
• £200 for WFH Setup.
• Private Medical Insurance including GP consultations (video, telephone or face‑to‑face), prescribed medication, in‑patient, day‑patient and out‑patient care, mental health support, optical, dental & audiological cover, physiotherapy, advanced cancer cover, menopause support.
• Employee Assistance Programme including unlimited mental health sessions, 24/7 remote GP & physiotherapy, 24/7 helpline for emotional & practical support.
• Savings & discounts on everyday shopping.
• 1:1 personalised well‑being consultations.
• Gym membership discounts.
• Hybrid Working.
• Casual dress code.
• Workplace socials.
• Healthy snacks.

Family Friendly Policies

• Enhanced maternity pay.
• Enhanced paternity pay.
• Enhanced adoption pay.
• Enhanced shared parental leave.

Learning & Development

• Professional Qualifications.
• Professional Memberships.
• Learning Suite for e‑courses.
• Internal Training Programmes.
• FCA & Regulatory training.