Tiger Analytics is hiring a
Data Scientist

Summary

Tiger Analytics is seeking a Principal Data Scientist with 5+ years of experience in supply chain optimization and inventory allocation to work on data science applications in the Retail and/or CPG industry. The role involves refactoring an Optimization algorithm, utilizing advanced statistical techniques, developing predictive models, collaborating with cross-functional teams, and staying updated on industry trends.

Requirements

• Proven experience 5+ years working as a Data Scientist, with a focus on supply chain optimization and inventory allocation
• MS or PhD in Computer Science, Operations Research, Applied Mathematics, Machine Learning, or a related field
• Experience with using mathematical programming solvers such as Gurobi, Xpress MP, CPLEX, or Google OR Tools in applications
• Solid understanding of statistical methods, optimization techniques, and predictive modelling concepts
• Strong proficiency in programming languages such as Python, Pyspark and SQL, and experience working with data analysis and machine learning libraries
• Ability to apply various analytical models to business use cases
• Exceptional communication and collaboration skills to understand business partner needs and deliver solutions and explain to business stakeholders

Responsibilities

• Refactor the Optimization algorithm written in Python using Object Oriented Programming
• Work on the latest applications of data science to solve business problems in the Supply chain and optimization space of Retail and/or CPG
• Utilize advanced statistical techniques and data science algorithms to analyze large datasets and derive actionable insights related to replenishment optimization and inventory allocation
• Develop and implement predictive models and optimization algorithms to improve inventory management, reduce stockouts, and optimize resource allocation across the supply chain
• Collaborate with cross-functional teams to understand business requirements and translate them into data-driven solutions
• Design and execute experiments to evaluate the effectiveness of different replenishment strategies and allocation policies
• Monitor and analyze key performance indicators (KPIs) related to replenishment and supply chain allocation, and provide recommendations for continuous improvement
• Stay abreast of industry trends and best practices in data science, replenishment optimization, and supply chain management, and leverage this knowledge to drive innovation within the organization
• Collaborate, coach, and learn with a growing team of experienced Data Scientists