Data Scientist (Supply Chain)

Role: - Supply Chain Data Scientist

Experience: - 5 Years

Notice Period: - 2 Months

Location: - LTM Pan India

Job Description:

The Supply Chain Data Scientist is responsible for applying AI, machine learning, advanced analytics, and statistical modelling to solve complex supply chain problems. This role partners with supply chain, operations, procurement, logistics, and IT teams to improve demand forecasting, inventory optimization, network design, and end to end supply chain visibility through AI and data driven insights.

Key Responsibilities

Develop and deploy AI/ML predictive and prescriptive models for demand forecasting, inventory optimization, replenishment, capacity planning, supplier risk analytics, logistics optimization, network design and margin analysis.

Analyse large, complex supply chain datasets from ERP, planning, logistics, and external sources to identify patterns, risks, and opportunities.

Build scenario simulations and what if analyses to support supply chain decision making.

Apply advanced statistical techniques and machine learning algorithms to improve forecast accuracy and service levels.

Translate business problems into scalable analytical solutions.

Productionize models and continuously improve them based on business feedback and changing conditions.

Required Qualifications

38+ years of experience in data science and AI with strong exposure to supply chain domains.

Hands on experience with real world supply chain data and planning processes.

Exposure to AI/ML model deployment (MLOps).

Strong proficiency in Python or R; strong SQL skills.

Expertise in ML techniques (regression, time series, clustering, optimization).

Experience with cloud analytics platforms (Azure, AWS, GCP).

Familiarity with visualization tools (Power BI, Tableau, or similar).

Preferred Qualifications

Experience with SAP (IBP, APO, ECC, S/4HANA) or other enterprise planning systems.

Knowledge of optimization solvers (e.g., linear programming, mixed integer programming)

Experience with data lakes, data fabrics, or modern analytics architectures.

Background in consulting or large-scale transformation programs.

Key Competencies

Strong AI and analytical problem-solving mindset.

Ability to translate complex data into supply chain decisions.

Excellent communication and stakeholder management skills.