I&F Decision Sci Practitioner Specialist

I&F Decision Sci Practitioner Specialist

Skill required: Delivery - HR Analytics
Designation: I&F Decision Sci Practitioner Specialist
Qualifications:Any Graduation
Years of Experience:7 to 11 years
About Accenture
Accenture is a global professional services company with leading capabilities in digital, cloud and security.Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Technology and Operations services, and Accenture Song— all powered by the world’s largest network of Advanced Technology and Intelligent Operations centers. Our 784,000 people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries. We embrace the power of change to create value and shared success for our clients, people, shareholders, partners and communities.Visit us at www.accenture.com
What would you do? Accenture is a global professional services company with leading capabilities in digital, cloud and security. Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Technology and Operations services, and Accenture Song— all powered by the world’s largest network of Advanced Technology and Intelligent Operations centers. Our 699,000 people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries. We embrace the power of change to create value and shared success for our clients, people, shareholders, partners and communities. Visit us at www.accenture.com. 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 • 6–9 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