People Data Scientist

This is a hybrid role working 3 days a week in the office and 2 from home. Key Responsibilities * 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 - https://youtu.be/TCMtTYUUiuU

• 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

#LI-CF1 Function People Country United Kingdom Office Location Newcastle Work Place type Hybrid Advert Working at Sage means you're supporting millions of small and medium sized businesses globally with technology to work faster and smarter. We leverage the future of AI, meaning business owners spend less time doing routine tasks, like entering invoices and generating reports, and more time pursuing their ambitions.

Our colleagues are the best of the best. It's why we were awarded 2024 Best Places to Work by Glassdoor. Because to achieve extraordinary outcomes, we need extraordinary teams. This means infusing Sage with people who knock down barriers, continuously innovate, and want to experience their potential. Learn more about working at Sage: sage.com/en-gb/company/careers/working-at-sage/ Watch a video about our culture: youtube.com/watch?v=qIoiCpZH-QE