Lead Data Scientist

About the job

Who we are

VOIS (Vodafone Intelligent Solutions) is a strategic arm of Vodafone Group Plc, creating value for customers by delivering intelligent solutions through Talent, Technology & Transformation.

As the largest shared services organisation in the global telco industry with 30,000 FTE, our portfolio of next-generation solutions and services are designed in partnership with customers across Vodafone Group, local markets, and partner markets to simplify and drive growth. With our strategic partner Accenture, we work alongside our Vodafone customers, other Telco and tech companies to drive transformation, meet the challenges of our industry and ensure we stay relevant and resilient. This partnership is a unique, industry-first model which brings together the best of in-house and 3rd party capability.

We work with customers across 28 countries from 10 VOIS locations: Albania, Egypt, Hungary, India, Romania, Spain, Turkey, UK, Germany, Ireland, and with a network of teams in Czech Republic, Italy, Greece, and Portugal.

#VOIS #BeUnrivalled #CreateTheFuture

About this role

We are seeking a Lead Data Scientist to provide senior scientific leadership for Data Science and applied-model development within Digital Engineering, Digital & IT.

Based flexibly in Newbury or Paddington, UK, you will translate customer, commercial and operational challenges into testable analytical approaches, lead modelling and experimentation, and ensure models are statistically sound, reproducible, explainable and fair.

Reporting to the Data Products & Insights Lead, you will define what should be modelled and how scientific validity should be established. You will work closely with Product, Data Engineering and ML & AI Engineering, with the Senior ML & AI Engineer responsible for reliable production engineering.

This role has no direct or dotted-line reports and is focused on scientific leadership, technical judgement and measurable real-world impact.

What you’ll do

• Frame customer, commercial and operational challenges as testable Data Science questions, defining outcomes, baselines, assumptions, decision thresholds and measures of value.
• Lead the development and validation of predictive, forecasting, propensity, anomaly and fraud, optimisation and causal models for prioritised use cases.
• Define appropriate experimental design, sampling approaches, feature strategies, evaluation methods and statistical tests based on the decision being supported and the available data.
• Lead modelling, experimentation and scientific validation, ensuring analytical approaches are proportionate to the problem and evidence available.
• Set and assure scientific standards for reproducibility, peer review, explainability, fairness, bias, uncertainty and model limitations.
• Evaluate model validity and recommend whether models should proceed, be redesigned or stop where sufficient validity or value cannot be established.
• Partner with Product, Data Engineering and ML & AI Engineering to ensure validated models are actionable and suitable for productionisation.
• Measure post-launch performance and real-world customer or business impact to establish whether deployed Data Science solutions are achieving their intended outcomes.
• Provide scientific input into data, tooling and experimentation choices.
• Support effective transition of scientifically validated models into reliable production environments while maintaining clear accountability between Data Science and ML/AI Engineering.

Who you are

You are an experienced Data Science practitioner with the technical depth and scientific judgement to lead complex modelling and experimentation in production-oriented environments.

You will bring:

• Extensive applied Data Science experience, including leadership of complex modelling and experimentation.
• Advanced Python capability and experience with relevant statistical and machine learning libraries.
• Advanced understanding of supervised and unsupervised machine learning, forecasting, causal inference and experimental methods.
• Experience selecting evaluation approaches, statistical tests, decision thresholds and validation techniques appropriate to different analytical problems.
• Strong understanding of model evaluation, calibration, explainability, fairness, bias, uncertainty and reproducibility.
• The scientific judgement to select proportionate approaches, communicate uncertainty clearly and recommend stopping or redesigning work where validity or measurable value cannot be demonstrated.
• Experience with cloud analytics and machine learning environments, preferably BigQuery and Vertex AI, or equivalent technologies.
• Strong working knowledge of production ML constraints and experience collaborating effectively with Data Engineers and ML & AI Engineers.
• The ability to convert customer, commercial and operational requirements into measurable analytical outcomes.
• Experience assessing deployed models against real-world customer or business outcomes.
• A postgraduate qualification in a quantitative discipline or equivalent depth of applied experience.

Not a perfect fit?

Concerned you may not meet every requirement? Vodafone is committed to creating an inclusive workplace where everyone can thrive. If you are excited about this role but your experience does not align exactly with every aspect of the job description, you are encouraged to apply. You may be the right candidate for this or another opportunity, and the recruitment team will support you in exploring where your skills fit best.

What's in it for you

• The opportunity to provide senior scientific leadership across Data Science and applied-model development.
• Work on customer, commercial and operational use cases spanning predictive modelling, forecasting, propensity, anomaly and fraud detection, optimisation and causal modelling.
• Influence whether Data Science use cases progress into production based on scientific validity, measurable value and real-world outcomes.
• Collaborate across Product, Data Engineering and ML & AI Engineering, helping connect scientific development with production-ready solutions.
• Shape scientific standards for responsible modelling, including reproducibility, explainability, fairness, bias and uncertainty.
• Work with cloud-based analytics and ML capabilities, including BigQuery and Vertex AI or equivalent technologies.
• Contribute to Data Science solutions designed to deliver measurable customer and business impact.

What skills you will learn

Through this role, you will have opportunities to further develop:

• Applied scientific leadership across complex Data Science and AI use cases.
• Advanced experimentation and causal inference, including experimental design, sampling, statistical evaluation and impact measurement.
• Responsible AI and model governance, with a focus on explainability, fairness, bias, uncertainty and reproducibility.
• Cloud-based Data Science and ML practices, including exposure to BigQuery and Vertex AI or equivalent environments.
• Production ML collaboration, working across Data Engineering and ML & AI Engineering to transition validated models into production.
• Post-launch model evaluation, connecting model performance with measurable customer and commercial outcomes.
• Business translation and scientific judgement, strengthening the ability to turn complex operational or commercial questions into testable hypotheses and evidence-based decisions.

VOIS Equal Opportunity Employer Commitment