Lead Data Scientist

Are you an experienced data scientist with a passion for building practical analytical solutions and turning complex data into meaningful insight?

As an individual contributor Lead Data Scientist within Workforce Strategy (WFS), you will take ownership of analytical projects that help Engineering understand and respond to its changing workforce needs.

Working with WFS leadership and cross-functional partners, you will turn agreed business questions into practical analytical solutions, scenario models and evidence-based insights that inform workforce decisions.

Your analysis will cover workforce size and shape, skills and capabilities, location and sourcing, and the implications of AI for work, productivity and capacity.

Responsibilities:

• Translate workforce questions into analytical approaches and build reusable solutions, including exploratory notebooks, scenario models and visualisations, to investigate capacity, role mix, skills, location, sourcing and cost.
• Connect and analyse workforce, financial, planning and delivery data to establish baselines, identify trends and dependencies, and test hypotheses.
• Investigate how AI and automation are changing activities, skills and capacity across developer and non-developer work.
• Apply and help improve consistent analytical methods, definitions and validation, working with data owners to resolve differences and explain limitations.
• Work with WFS leadership and business and technical partners to agree analytical priorities based on decision value and evidence availability, then take ownership of delivering the analysis.

Requirements:

• Bachelor’s degree in Engineering, Computer Science, Data Science, Statistics, Mathematics, Physics or related field, or equivalent work experience.
• Demonstrable experience independently delivering data science projects that address complex business questions, building practical analytical solutions and translating findings into useful insight and decision support.
• Strong exploratory data analysis and statistical skills, including hypothesis testing, segmentation, trend analysis and scenario modelling.
• Strong Python and SQL skills for preparing, connecting and analysing complex datasets, and developing statistical models, scenarios and clear visualisations.
• Excellent communication and stakeholder skills, with the ability to frame business questions, explain complex findings to non-technical audiences and manage analytical priorities in a rapidly changing environment.

Benefits:

• High-impact projects: Build analytical solutions and insights that help Engineering understand its workforce, explore future scenarios and make informed choices as technology and business needs evolve.
• Competitive benefits: You will enjoy a strong compensation package, comprehensive benefits, and ongoing investment in career growth and skill development.
• Contribute to an evolving capability: Help improve WFS’s analytical tools, methods and evidence base through practical delivery, bringing data science to questions about the future of work, skills and capacity.
• Collaborative environment: We provide opportunities for continuous learning and professional development in a work environment of dedicated, highly experienced teams.