Data Scientist, People & Culture, DIO

The company is seeking a seasoned Data Scientist to bolster its People & Culture team, specifically within the Workforce Insights division. This role is central to revolutionising how the organisation understands, plans for, and cultivates its talent pool. You will be instrumental in applying cutting-edge analytical techniques, including machine learning and Generative AI, to tackle intricate workforce-related issues.

About the Role

In this capacity, you will harness the power of advanced data science to derive meaningful insights from substantial datasets concerning people and culture. The primary objective is to build predictive models, AI-driven solutions, and actionable intelligence that will significantly influence key areas such as workforce planning, skill development, talent management strategies, organisational effectiveness, and the overall employee experience. You will collaborate closely with various stakeholders, including People & Culture specialists, business leaders, data engineers, and technology teams, to translate complex business challenges into robust, scalable analytical products. Your work will be pivotal in driving evidence-based decision-making and unlocking tangible business value.

Your responsibilities will encompass a broad range of data science activities focused on workforce optimisation:

• Develop and implement sophisticated analytical models, machine learning algorithms, and Generative AI solutions to address strategic workforce challenges.
• Construct predictive models and workforce intelligence tools designed to inform decisions related to talent acquisition, skills development, succession planning, productivity enhancements, and long-term workforce forecasting.
• Utilise platforms like Microsoft Fabric, OneLake, Power BI, and Azure AI services to engineer scalable, production-ready analytical solutions.
• Transform large, complex datasets related to the workforce into clear, actionable insights, compelling narratives, and essential support for executive decision-making.
• Champion and apply Responsible AI principles throughout the development lifecycle, ensuring that all solutions are ethical, transparent, secure, and compliant with relevant regulations.
• Work collaboratively with People & Culture departments and business leaders to identify opportunities where data science and AI can yield significant improvements in workforce outcomes and employee satisfaction.
• Contribute to the continuous improvement and evolution of the Workforce Insights function by introducing and embedding leading practices in AI, analytics, and decision intelligence.

What They're Looking For

To excel in this role, candidates should possess a strong academic background and extensive practical experience:

• A postgraduate qualification in a quantitative field such as Data Science, Statistics, Mathematics, Computer Science, Operations Research, Engineering, or Econometrics is required.
• A minimum of five to eight years of experience in Data Science, Advanced Analytics, or Machine Learning is essential.
• Demonstrated experience in developing and deploying machine learning solutions within cloud environments is a must.
• Proficiency in working with Microsoft Fabric, Azure, and modern enterprise data platforms is a key requirement.
• A proven track record of delivering measurable business impact through the application of AI, predictive analytics, and advanced modelling techniques.
• The ability to articulate complex analytical concepts and findings clearly to senior business stakeholders is crucial.
• While not strictly mandatory, prior experience within People & Culture, Workforce Analytics, Organisational Effectiveness, or related domains would be considered a significant advantage.

This role offers an exciting opportunity for a skilled Data Scientist to make a substantial impact on how a major organisation manages its most valuable asset: its people. The position demands a blend of technical expertise, strategic thinking, and collaborative ability, all geared towards driving informed, data-led decisions within a dynamic business environment.

Minimum qualifications
Postgraduate qualification in Data Science, Statistics, Mathematics, Computer Science, Operations Research, Engineering, Econometrics or a related quantitative discipline.

Experience required

• 5-8 years experience in Data Science, Advanced Analytics or Machine Learning, with demonstrated experience developing and operationalising machine learning solutions in cloud environments.
• Must have experience working with Microsoft Fabric, Azure and modern enterprise data platforms.
• Track record delivering business impact through AI, predictive analytics and advanced modelling with the ability to communicate complex analytical concepts to senior business stakeholders.
• Develop and deploy advanced analytics, machine learning and Generative AI solutions to address strategic workforce challenges.
• Build predictive models and workforce intelligence products that support talent, skills, succession, productivity and workforce planning decisions.
• Leverage Microsoft Fabric, OneLake, Power BI and Azure AI services to create scalable, production-ready solutions.
• Transform large and complex workforce datasets into actionable insights, compelling narratives and executive decision support.
• Apply Responsible AI principles, ensuring solutions are ethical, explainable, secure and compliant.
• Partner with People & Culture and business stakeholders to identify opportunities where data science and AI can improve workforce outcomes and employee experiences.
• Contribute to the evolution of the Workforce Insights function by introducing leading practices in AI, analytics and decision intelligence.
• Experience within People & Culture, Workforce Analytics, Organisational Effectiveness or related domains would be highly advantageous.

Behavioural Competencies:

• Adopting Practical Approaches
• Articulating Information
• Challenging Ideas
• Checking Things
• Examining Information
• Exploring Possibilities
• Interacting with People
• Interpreting Data
• Meeting Timescales
• Producing Output
• Providing Insights
• Team Working

Technical Competencies:

• Data Analysis
• Database Administration
• Data Integrity
• Knowledge Classification
• Research & Information Gathering