People Data Scientist

SAGE GROUP PLC; Newcastle upon Tyne; Hybrid; GBP 100,000 - 125,000; Full time

Job summary

A leading technology firm in Newcastle upon Tyne is seeking a Data Analyst to develop predictive and prescriptive people analytics models, translating workforce challenges into actionable insights. The ideal candidate will have strong skills in Python and SQL, alongside experience with HR data sources. This hybrid role offers generous bonuses, enhanced parental leave, and a comprehensive benefits package, ensuring work-life balance and support for professional growth.

Benefits

Generous bonuses and pension scheme

25 days of paid annual leave

Paid 5 days yearly to volunteer

Enhanced parental leave

Comprehensive health, dental, and vision coverage

Work away scheme for up to 10 weeks a year

Access to memberships for finances, health and wellbeing

Qualifications

• Experience in exploratory data analysis and predictive modelling.
• Familiarity with vector databases and prompt engineering.
• Understanding of ethical AI principles and responsible AI practices.

Responsibilities

• Develop predictive analytics models addressing various workforce challenges.
• Partner with teams to design scalable data pipelines and deploy ML/AI models.
• Create dashboards that provide workforce insights.

Skills

Strong proficiency in Python (Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow)

SQL

Experience with HR data sources (Workday, SuccessFactors, Oracle HCM)

Knowledge of people analytics methodologies

Familiarity with big data frameworks (Spark, Databricks, Dask)

Familiarity with MLOps principles

Strong understanding of machine learning algorithms

Experience with data visualisation tools (Tableau, Power BI)

Education

Degree in a quantitative discipline (applied mathematics, statistics, computer science)

Tools

Tableau

Power BI

Snowflake

AWS

Azure

GCP

Job description

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 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