Transport for London
Data Scientist - ML Ops
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Job title: Data Scientist
Salary: £72-85k
Grade: Band 3
Contract type: TfL Reference: 5544
Contract details: FTC – 12 months Location: Pier Walk, North Greenwich
Application closing date: 8/9/2026 at 23:59
All offers of employment are subject to satisfactory right-to-work checks. Candidates must be able to demonstrate their right to work in the UK. At the present time TfL is unable to offer visa sponsorship for this role.
Hybrid working within this role enables a balance of 50 per cent of time split between the office and home over a 4-week period. Hybrid working arrangements can evolve subject to business requirements.
Overview Of Project/role
The Data Scientist will collaborate closely with the Lead Data Scientist and Principal Data Scientist and cross-functional teams to design, deliver and continually enhance advanced data-driven solutions and analytical insights for TfL. You'll prepare, structure and analyse diverse datasets (structured and unstructured) to ensure they're robust, reliable and fit for analytical purposes, including suitability for leveraging AI and Generative AI techniques.
Your role requires you to apply statistical, mathematical and scientific methods including exploratory data analysis, predictive modelling, machine learning, deep learning, hypothesis testing, optimisation techniques and emerging Generative AI methodologies to extract meaningful insights that inform strategic and operational decisions. You'll confidently evaluate analytical models and methodologies, refining and validating their effectiveness, with particular attention to optimising the performance of machine learning models.
You'll engage proactively with stakeholders to define business problems clearly and translate them into analytical projects. Your strong communication skills will ensure that complex findings are presented clearly through compelling visualisations and narratives, tailored to technical and non-technical audiences alike, highlighting potential applications of AI-driven solutions.
As part of your responsibilities, you'll explore innovative analytical techniques, contributing to TfL’s culture of continuous learning and improvement, including staying abreast of advancements in AI and Generative AI. You'll also promote adherence to best practices (including ethical standards) for model training and development, deployment and performance monitoring.
Key Responsibilities
- Build, test and iteratively refine scripts and algorithms using data science programming best practices, including version control and reproducibility and developing in, and helping to shape, an ML Ops framework and environment
- Develop robust analytical solutions and algorithms from extensive customer and operational datasets, including ticketing, sensor, telemetry and vehicle log data.
- Integrate and analyse complex datasets to derive actionable insights supporting key operational and strategic decisions across TfL.
- Ensure the practical application of analytical findings, providing development teams with clear methodologies ready for implementation, including applications leveraging AI and machine learning.
- Identify operational efficiencies and opportunities for improvement through rigorous analytical approaches.
- Research, prototype, test and enhance innovative approaches in machine learning, deep learning, AI and Generative AI.
- Actively promote best practices and standardisation within TfL’s data science community.
- Work collaboratively with data engineers and architects to ensure efficient, reliable data pipelines and identify opportunities to enhance data quality and accessibility.
- Develop a clear understanding of product delivery methods, including agile methodologies and machine learning Ops, and apply these principles to manage priorities effectively.
- Collaborate closely with product managers and other specialists to define requirements for a data science solution ensuring alignment with product goals and business objectives.
- Actively participate in the development and mentorship of data science graduates and associate data scientists, fostering a culture of learning and capability growth within the data science team.
- Respond to ad-hoc analytical requests, providing quick-turnaround insights to operational colleagues when necessary.
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Knowledge
- Experience of developing and delivering products and analyses through a ML Ops environment, and experience of shaping the framework for ML Ops.
- Proficiency in statistical programming languages (Python, R) and familiarity with relevant and modern-day libraries and frameworks.
- Thorough understanding of statistical methods, machine learning, deep learning, simulation, optimisation and hypothesis testing.
- Experience scoping analytical solutions aligned with business challenges.
- Strong awareness of data governance, ethics and compliance, including GDPR and Data Protection Act requirements, along with a solid understanding of the ethical implications and governance challenges posed by AI and emerging technologies
- Familiarity with London's transport landscape and challenges.
Skills
- Ability to develop data science outputs and products in an ML OPS environment
- Ability to extract actionable insights from complex, large-scale datasets through rigorous analysis.
- Advanced capability in predictive analytics and the application of machine learning, deep learning and emerging AI techniques to solve complex business problems.
- Clear and impactful communication skills, including presenting findings and complex concepts effectively to stakeholders across varying technical skill levels.
- Ability to frame business problems clearly and design effective analytical solutions.
- Collaborative working style, effectively engaging with multidisciplinary teams and stakeholders.
- Strategic awareness and the ability to understand and communicate the wider business implications of analytical results.
- Proactive, data-driven problem-solving approach.
Experience
- Experience in the development and delivery of the foundation principles surrounding MLOps, including collaborative model optimisation, deployment and monitoring in production environments.
- Proven track record of delivering impactful analytical solutions in collaboration with stakeholders.
- Extensive experience handling and analysing large, complex datasets to inform significant business decisions.
- Demonstrable experience influencing strategic decisions through analytics, machine learning, or AI solutions.
- Experience clearly communicating analytical findings to diverse audiences.
- Experience with cloud-based analytical platforms (Azure, AWS, Google Cloud).
- Hands-on experience with deep learning, image processing, NLP and familiarity with platforms like Databricks.
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Additional Role Overview
Responsibilities will include conducting exploratory and hypothesis-driven analyses, applying advanced analytical methods and enhancing existing capabilities, particularly around predictive analytics and AI. You will communicate analytical outcomes clearly, provide strategic recommendations and proactively identify opportunities for innovation and improvement in data-driven decision-making processes across TfL.
Application Process
Please apply using your CV only and a covering letter. Think carefully about the skills, knowledge and experience in the advert and cover this in your CV PDF format preferred and do not include any photographs or images
Equality, diversity and inclusion
We are committed to equality, diversity and inclusion. We want to represent the city we serve, which will help us become a more innovative and efficient organisation. Our goal is to make our recruitment as inclusive as possible. We are a disability confident employer who guarantee an interview to any disabled candidate who meets all of the essential criteria. We also use anonymising software that removes identifying information from CVs and cover letters to make the process fair.
Benefits
In return for your commitment and expertise, you will enjoy excellent benefits and scope to grow. Rewards vary according to the level of role but mostly include the below:
- Final salary pension scheme
- Free travel for you on the TfL network
- Reimbursement of 75% of the cost of a standard class Ticket for National Rail travel from home
- 30 days annual leave plus public and bank holidays
- TfL is committed to work-life balance, operating a hybrid working approach where business and role requirements allow
- Private healthcare discounted scheme (optional)
- Tax-efficient cycle-to-work programme
- Retail, health, leisure and travel offers
- Discounted Eurostar travel
We will make every effort to give you as much notice as possible, however some interviews/assessments could be organised at short notice.
Vetting Process
At Transport for London, safety, trust and fairness sit at the heart of how we recruit. Our Vetting Charter (https://tfl.gov.uk/corporate/careers/our-vetting-process) explains the checks we carry out before you join us, helping ensure we create a safe, inclusive and reliable network for everyone who depends on our services. We simply ask that the information you provide is honest and accurate so we can progress your application smoothly. If something doesn’t match or can’t be verified, we may not be able to move forward with your application, but we’ll always treat you with transparency, respect, and clear communication throughout.
We may close this advert early if we receive a high volume of suitable applications.
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