Consultant - Advanced Analytics, GIC SC Analytics

Supply chain analytics group is responsible for delivering the solutions and developing the capabilities which enables better decision-making in supply chain This role is in the Segment analytics team that supports the Segment teams by developing advanced analytics solutions to identify and analyze opportunities corresponding to variety of SC Analytics problem statements. The primary responsibilities of this job are to develop innovative solutions by leveraging analytics techniques like descriptive, diagnostic, predictive and prescriptive modeling, statistical analysis and operations research techniques. This is an individual contributor role that includes project lead responsibilities, stakeholder management, project management, coaching and mentoring the analysts in the team. This role requires to operate in 1.30pm to 10.30 pm shift.

KEY ACCOUNTABILITIES

Requirement Gathering and Project Management (20% of Time)

Partner with supply chain stakeholders to understand business decisions, operational context, constraints, and desired outcomes, translating ambiguous questions into clear analytical problems, hypotheses, scope, and success measures.

Select the right approach—statistical analysis, machine learning, forecasting, experimentation, or operations research—while assessing data readiness, risks, dependencies, feasibility, priorities, and milestones.

Analytics Models design, development & Improve (40% of Time)

Ideate and execute improvements that drive efficiency, standardization, and scalable solutions through historical data analysis and machine learning.

Develop analytical models across descriptive, diagnostic, predictive, and prescriptive analytics, including feature engineering and automated testing.

Explain and deploy model recommendations to cross-functional stakeholders while supporting enhancements and bug fixes for existing models.

Output (20% of Time)

Provide actionable insights through effective presentations and visualizations while deploying, documenting, and sustaining models and applications using DevOps/MLOps practices.

Training / Knowledge (20% of Time)

Mentor and train team members in data preparation, diagnostics, predictive analytics, R, Python, and supply chain analytics.

Standardization and document processes, working on individual development plans, and contribute to data science processes, frameworks, tools, and standards.