OpenOpportunity Sourced Jobs — Bengaluru, Pune, Gurugram
Full Time · On Site · Leadership
Role: Supply Chain Manager | Department: Procurement & Supply Chain | Industry: Analytics / KPO / Research | Education: UG: Any Graduate; PG: Any Postgraduate Job description Data Science Managers (DSMs) design, develop and execute analytic techniques on large, complex, structured and unstructured data sets (including big data) to help clients make better fact-based decisions. DSMs will develop new offerings/solutions, drive client impact by delivering client solutions and shape the ZS point of view in this space. You will be responsible for applying analytical techniques to model complex business problems, uncovering insights, and identifying opportunities using statistical, algorithmic, mining, and visualization techniques. What You'll Do: • Drive client engagements and lead end-to-end development/deployment of AI/ML/data science solutions as per client requirement. • Lead large scale client delivery engagements in AI projects for the Supply Chain Manufacturing Industry. • Architect and develop predictive models, optimization algorithms, and statistical analyses. • Lead and mentor a team of data scientists, providing guidance and support to ensure the successful execution of client projects. • Drive business and strategy development through project delivery and client relationship management. • Develop/sell new business opportunities. • Direct multiple projects simultaneously, honing analytic and project management skills. • Play a key role in development of data science capabilities and offerings that create scale and advance our analytic platform. • Motivate, coach and serve as a role model for project team members. • Provide thought leadership and innovation through research and publication. What You'll Bring: • PhD degree in Computer Science, Statistics or related discipline; 8+ years of relevant post-collegiate work experience; in lieu of a PhD, 10+ years of work experience may substitute. • Hands-on experience in applying advance analytics leveraging techniques of AI, ML to Supply Chain areas like Demand Planning, Forecasting, Supply Planning, Inventory Management, Logistics. • Experience leading a team of data scientists, data engineers, domain experts, LLM engineers, DevOps across multiple projects. • Experience with big data, claims analytics, advanced analytics concepts and algorithms (e.g. text mining, social listening, recommender systems, predictive modeling, Gen AI, proficiency with large language models etc.). • Relevant programming background (e.g. Python/R). • Proven track record of business development. • Agile project planning and project management experience. • Team management and skill development experience. • Relevant domain knowledge preferred (healthcare, pharma). • Excellent oral and written communication skills. • Strong attention to detail, with a research-focused mindset. • Excellent critical thinking and problem solving skills. Note: The live posting has an apostrophe-stripping artifact ("What Youll Do" / "What Youll Bring" instead of "What You'll Do" / "What You'll Bring," restored here), the same systemic text-processing bug seen in ZS Associates' other Naukri listings across earlier batches. Despite the job title explicitly naming "Supply Chain & Manufacturing," the "preferred domain knowledge" listed is "healthcare, pharma" - domains with no connection to supply chain or manufacturing, apparently carried over from a different ZS template (ZS Associates is well known for pharma/healthcare analytics work). Role is tagged "Supply Chain Manager," which undersells what is fundamentally a data science/AI leadership role rather than an operational supply-chain management position. Originally posted on Naukri: https://www.naukri.com/job-listings-data-science-manager-supply-chain-manufacturing-zs-associates-india-pvt-ltd-pune-gurugram-bengaluru-10-to-15-years-170826919927
data science, python, project management, supply chain, forecasting, ai, llm, machine learning, artificial intelligence, r, predictive modeling, devops, manufacturing, agile, big data