Data Scientist

Data Scientist

JPS Tech Solutions is looking for an experienced Data Scientist to focus on supply chain optimization and inventory allocation.

Job Category:
Data Scientist

Job Type: Onsite (W2-Contract Only). Applications on a C2C basis will not be considered.

Job Location:

Dallas, Texas

Compensation:
Depends on Experience

Seniority level:
Mid-Senior level

• Responsible for refactoring 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.

• Proven experience 10+ 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.