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 explicit, 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

📌 I&F Decision Sci Practitioner Specialist (Karnataka)
🏢 Accenture
📍 Karnataka