Our client is looking for an experienced Data Science Lead to drive advanced analytics, AI/ML initiatives, and data-driven transformation programs. This role offers an exciting opportunity to lead a high-performing team, develop scalable analytics solutions, and partner with global stakeholders to deliver measurable business impact across manufacturing, operations, and supply chain functions.
Key Responsibilities
Data Science & Analytics Leadership
- Lead the design and delivery of advanced analytics and machine learning solutions.
- Drive high-impact use cases focused on:
- Manufacturing productivity improvement
- Process optimization and operational efficiency
- Quality, yield, downtime, and cost optimization
- Predictive, prescriptive, and simulation-based analytics
- Own the end-to-end analytics lifecycle, including problem definition, data exploration, model development, validation, deployment, and performance monitoring.
Hands-on Technical Delivery
- Develop and review machine learning and statistical models using Python and SQL.
- Build Proof of Concepts (PoCs) and scalable analytics solutions leveraging:
- Azure Cloud
- Azure Data Factory (ADF)
- Snowflake
- Collaborate with data engineering and platform teams to productionize analytics solutions.
- Ensure model robustness, explainability, and business relevance.
Team Leadership & Capability Building
- Lead, mentor, and develop a team of Data Scientists and Analysts.
- Establish best practices, reusable frameworks, and technical standards.
- Conduct code reviews, model reviews, and technical design discussions.
- Drive capability building and continuous learning within the team.
Stakeholder Management
- Partner with global business, operations, manufacturing, R&D, and digital teams.
- Translate business challenges into structured analytics opportunities.
- Present insights, recommendations, and value realization outcomes to senior leadership.
- Act as a key bridge between business objectives and analytics execution.
Required Skills & Experience
Technical Skills
- Strong hands-on expertise in Python (Pandas, NumPy, Scikit-Learn, Statsmodels, etc.)
- Advanced SQL skills
- Experience with:
- Azure Cloud
- Azure Data Factory (ADF)
- Snowflake
- Strong understanding of:
- Machine Learning
- Statistical Modeling
- Optimization Techniques
- Forecasting and Time-Series Analytics
- Operational Analytics
- Experience deploying enterprise-scale analytics solutions from PoC to production.
Domain Experience
- Experience in Manufacturing, Industrial Analytics, Operations, Productivity Improvement, or Supply Chain Analytics.
- Strong business acumen with the ability to quantify ROI and business impact.
Leadership Skills
- Proven experience leading Data Science or Analytics teams.
- Strong communication, stakeholder management, and problem-solving capabilities.
- Ability to thrive in a global, matrixed environment.
Qualifications
- Bachelor's or Master's degree in Engineering, Computer Science, Statistics, Mathematics, Data Science, or a related field.
- 8–14+ years of overall experience in Data Science, Analytics, or AI/ML.
- 3–5+ years of experience leading Data Science or Advanced Analytics teams.
- Experience working within GCC, CoE, or global delivery environments is preferred.
