Senior/Lead Data Scientist (Supply Chain)
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Job Description
Tiger Analytics is looking for experienced Data Scientists to join our fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world.
As a Senior/Lead Data Scientist with strong expertise in advanced data processing to join our Supply Chain Analytics team. The ideal candidate will have hands-on experience leveraging Python, PySpark, modelling and EDA experience solve complex business problems in supply chain optimization.. You will develop efficient and accurate analytical models which mimic business decisions and incorporate those models into analytical data products and tools. You will have the opportunity to drive current and future strategy by leveraging your analytical skills as you ensure business value and communicate the results.
Key Responsibilities
- 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
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