People Data Scientist
Sage
- Newcastle upon Tyne, England, United Kingdom
- Newcastle upon Tyne, England, United Kingdom
About
Role Summary: Join the People Analytics Centre of Excellence and help transform how we understand and leverage workforce data across the business. In this hybrid role (3 days in office, 2 days remote), you will 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.
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 organizational network analysis, 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.
Skills & Requirements
Strong proficiency in Python (Pandas, NumPy, Scikit‑learn, PyTorch/TensorFlow) and SQL.
Experience working with HR data sources (Workday, SuccessFactors, Oracle HCM, LinkedIn Talent Insights) 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 & business data.
Familiarity with MLOps principles, CI/CD, and deploying ML/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 NLP, 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.
Technical / Professional Qualifications
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 (UK)
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 the 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.
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Languages
- English
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