Job Description
Skill required: Delivery - HR Analytics
Designation: IF Decision Sci Practitioner Specialist
Qualifications:Any Graduation
Years of Experience:7 to 11 years
What would you do Intelligent Operations centers. We embrace the power of change to create value and shared success for our clients, people, shareholders, partners and communities. .
The Data Science Consultant (CL9) is a senior individual contributor and de facto technical lead for the People Analytics data science workstream. This role is fully accountable for the end-to-end lifecycle of predictive models and advanced analytics use cases - from problem framing and feature engineering through to model deployment and insight communication. The CL9 requires minimal managerial intervention, independently manages stakeholder interactions on technical matters, and is the go-to expert for complex, ambiguous analytics challenges.
What are we looking for A. Advanced Data Science ML Skills
End-to-end ML lifecycle ownership
Feature engineering model pipelines
Advanced algorithms (XGBoost, LightGBM, etc.)
Strong understanding of Workday and data manipulation in Power BI environment
B. Statistical Analytical Skills
Survival analysis (attrition modelling)
Regression, classification, clustering
Causal inference techniques
C. Programming Tools
Python (expert: pandas, sklearn, numpy)
ML platforms (Databricks, SageMaker, Azure ML)
D. People Analytics Expertise
Attrition / flight risk models
Workforce demand forecasting
Hiring success prediction
E. Responsible AI Skills
Bias detection mitigation
Model fairness explainability
F. Business Translation Skills
Data storytelling for HR leaders
Translating insights decisions
69 years of experience in data science, applied ML, or workforce analytics with end-to-end model ownership
Expert proficiency in Python (scikit-learn, XGBoost, LightGBM, statsmodels, pandas, NumPy)
Strong grounding in statistical methods: survival analysis, classification, regression, clustering, causal inference
Experience translating model outputs to non-technical audiences; strong data storytelling skills
Familiarity with cloud ML platforms (Azure ML, AWS SageMaker, Databricks) and MLOps principles
HR domain knowledge across talent acquisition, attrition, workforce planning, and learning development
Master s degree in data science, Statistics, Industrial-Organizational Psychology, Economics, or related quantitative field strongly preferred
Roles and Responsibilities: Own the full lifecycle of predictive analytics use cases: problem scoping, data collection, feature engineering, modelling, validation, and deployment
Build and maintain production-grade predictive models for attrition risk, flight risk, performance prediction, hiring success, and workforce demand forecasting
Lead scenario planning analyses that quantify workforce supply-demand gaps and support strategic headcount decisions
Develop and maintain a library of reusable assets: feature stores, modelling templates, evaluation frameworks, and scoring pipelines
Translate complex model outputs into clear, actionable narratives for HR and business leaders
Review and provide technical mentorship on the work of the CL10 Data Science Senior Analyst
Proactively identify new use cases where advanced analytics can drive HR value; propose approaches to the Analytics Partner
Ensure model fairness, bias auditing, and responsible AI practices across all workforce models
Contribute to data science best practice documentation and knowledge-sharing within the team
Qualification Any Graduation
