People Data Scientist
Job Description
Join our People Analytics Centre of Excellence and help transform how we understand and leverage workforce data across the business. In this role, you'll build advanced analytics, machine learning models, and AI-driven solutions that empower leaders to make evidence-based decisions about talent, performance, and the future of work.
This is a hybrid role working 3 days a week in the office and 2 from home.
Benefits video –
Join our People Analytics Centre of Excellence and help transform how we understand and leverage workforce data across the business. In this role, you'll build advanced analytics, machine learning models, and AI-driven solutions that empower leaders to make evidence-based decisions about talent, performance, and the future of work.
This is a hybrid role working 3 days a week in the office and 2 from home.
- Develop predictive and prescriptive people analytics models (attrition, skills, workforce planning, D&I insights, forecasting).
- Translate workforce challenges into experiments, insights, and actionable recommendations.
- Build AI-powered HR solutions, including NLP, generative AI, and LLM applications.
- Conduct ONA, workforce segmentation, and employee sentiment analysis.
- Partner with HRIS, engineering, and business teams to design scalable data pipelines and deploy ML/AI models.
- Create dashboards and visualisations that bring workforce insights to life for leaders.
- Support evidence-based decision-making across HR and the wider business.
- Strong proficiency in Python (Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow, and experience with AI frameworks for deep learning and generative models) and SQL.
- Experience working with HR data sources (Workday, SuccessFactors, Oracle HCM, LinkedIn Talent Insights, etc.) or related workforce datasets.
- Knowledge of people analytics methodologies such as attrition modelling, pay equity analysis, employee lifetime value, skills inference, or organisational network analysis.
- Familiarity with big data frameworks (Spark, Databricks, Dask) and cloud platforms (AWS, Azure, GCP).
- Knowledge of Snowflake and experience integrating with HR and business data.
- Familiarity with MLOps principles, CI/CD, and deploying ML and AI models in production environments, including monitoring and retraining pipelines.
- Strong understanding of machine learning algorithms for classification, regression, clustering, and time series forecasting, plus exposure to advanced AI techniques such as natural language processing (NLP), large language models (LLMs), and generative AI.
- Experience with data visualisation tools (Tableau, Power BI, or Python-based libraries).
- Excellent problem-solving skills and ability to translate complex technical analyses into clear, actionable insights for non-technical audiences.
- Familiarity with vector databases, embedding-based retrieval, and prompt engineering to support AI-enabled HR solutions.
- Understanding of ethical AI principles, bias detection, and responsible AI practices in HR contexts.
- Degree in a quantitative discipline (applied mathematics, statistics, computer science, economics, organisational psychology, or related field).
- Demonstrable experience in exploratory data analysis, feature engineering, and predictive modelling.
- Experience with Python, Scikit-learn, and PyTorch. Ideally with exposure to PySpark, Snowflake, AWS, and GitHub (MLOps practices).
- Knowledge of AI model evaluation techniques, including prompt optimisation and performance benchmarking.
Benefits video –
- Generous bonuses and pension scheme: Up to 8% matched pension contribution plus 2% top-up by Sage.
- 25 days of paid annual leave with the option to buy up to another 5 days
- Paid 5 days yearly to volunteer through our Sage Foundation
- Enhanced parental leave
- Comprehensive health, dental, and vision coverage
- Work away scheme for up to 10 weeks a year
- Access to various helpful memberships for finances, health and wellbeing