As a Data Scientist, you will lead digital transformation initiatives in supply chain and procurement areas, work closely with business leaders, operations teams, and IT stakeholders, develop and deploy advanced analytics solutions to enhance supply chain efficiency, forecast demand, optimize inventory, and automate decision-making. You will also drive program execution, ensuring that insights and automation solutions are seamlessly integrated into business operations. This role requires strong analytical expertise, strategic thinking, and program management skills. ESSENTIAL DUTIES AND RESPONSIBILITIES: Demand Forecasting & Planning Develop predictive demand forecasting models using time-series analysis, ML, and deep learning. Improve forecast accuracy by integrating external data sources (macroeconomic trends, supplier risks). Supply Chain Process Automation & Optimization Design and deploy robotic process automation (RPA) tools across supply chain and procurement processes. Build end-to-end data streaming system for visualization. Leverage optimization algorithms for procurement, supplier selection, and sourcing strategies. Automate supply risk prediction models to proactively mitigate disruptions. Optimize transportation networks, warehouse operations, and route planning using ML-based models. Implement AI-driven cost and sustainability optimization models. Intelligent Decision Support & AI Governance Build AI-powered decision support systems for supply chain leaders. Establish explainable AI frameworks to ensure transparency in supply chain decision-making. Communicate data-driven recommendations to business and executive stakeholders via dashboards and reports Program Management & Stakeholder Engagement Lead cross-functional programs to drive AI and automation adoption in supply chain processes. Manage project timelines, resource allocation, and risk mitigation for AI/ML-driven supply chain initiatives. Drive change management and process adoption strategies to ensure successful deployment of AI solutions.
REQUIRED: Bachelor’s degree in computer science, data science, AI/ML, supply chain analytics, or a closely related field. A master’s degree is highly desirable. A minimum of 5 years of relevant industry experience in analytics/data science. PREFERED: Experience in GenAI for supply chain (LLMs for process automation, NLP for contract analysis). Knowledge of IoT & digital twins for real-time supply chain visibility. Full stack development experience is preferred. Familiarity with a CI/CD pipeline. Experience with containerization technologies, such as Docker, and orchestration with Kubernetes. Familiarity with code versioning tools, such as Git. Experience with cloud platforms (AWS, GCP, Azure) and big data tools (Spark, Databricks, Snowflake). SKILLS: Strong expertise in Python, R, SQL, and ML frameworks (TensorFlow, PyTorch, Scikit-learn). Hands-on experience with time-series forecasting (ARIMA, LSTM, Prophet, XGBoost, etc.). Expertise in optimization algorithms (linear programming, heuristic methods, reinforcement learning). Experience working with ERP, SCM, and logistics systems (SAP, Oracle etc.). Strong understanding of supply chain KPIs, network design, and logistics processes. Ability to translate complex data insights into business impact. Strong communication and collaboration skills with cross-functional teams.
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