Collaborate with business partners to develop innovative solutions to meet objectives utilizing cutting edge techniques and tools.
Design and implement graph-based models to analyze, optimize, and improve supply chain networks.
Apply advanced data science techniques to identify patterns, inefficiencies, and bottlenecks across logistics and operations.
Build scalable data pipelines and analytical models using PySpark for large-scale supply chain datasets.
Develop predictive and prescriptive models to support decision-making in areas such as demand forecasting, routing, and inventory management.
Collaborate with cross-functional teams including operations, product, and engineering to translate business challenges into analytical solutions.
Communicate insights and recommendations clearly to stakeholders through data storytelling, visualizations, and presentations.
Share your passion for Data Science with the broader enterprise community; identify and develop long-term processes, frameworks, tools, methods and standards.
Collaborate, coach, and learn with a growing team of experienced Data Scientists.
Stay connected with external sources of ideas through conferences and community engagements

8+ years of professional experience in Data Science, Analytics, or related roles.
Strong programming skills in Python with demonstrated use of scientific computing libraries (NumPy, Pandas, SciPy, scikit-learn, etc.).
Experience with PySpark for large-scale data processing and analytics.
Practical exposure to supply chain domain problems such as logistics, distribution networks, or demand planning.
Strong analytical, problem-solving, and communication skills.
Experience developing models from inception to deployment

This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.

Senior/Lead Data Scientist – Supply Chain

Key skills