JPS Tech Solutions
Job Title:
Data Scientist
Location:
Omaha, Nebraska
Experience Required:
12+ Years
Key Responsibilities
Refactor and enhance existing optimization algorithms written in Python using object‑oriented programming principles.
Apply advanced data science techniques to solve business problems in supply chain optimization and retail/CPG inventory planning.
Analyze large and complex datasets using statistical methods and machine learning models to generate insights for replenishment and inventory allocation.
Develop, deploy, and maintain predictive models and optimization algorithms to improve inventory management, reduce stockouts, and optimize resource utilization.
Collaborate with cross‑functional teams to translate business requirements into scalable, data‑driven solutions.
Design and execute experiments to assess the effectiveness of replenishment strategies and allocation policies.
Monitor key supply chain performance metrics, evaluate model performance, and make recommendations for continuous improvement.
Stay updated on industry trends, tools, and best practices in data science, optimization, and supply chain management.
Mentor and collaborate with other data scientists to promote knowledge sharing and skill development.
Qualifications
Minimum 12+ years of professional experience as a Data Scientist, ideally within supply chain optimization or inventory allocation.
Master's or Ph.D. in Computer Science, Operations Research, Applied Mathematics, Machine Learning, or a related discipline.
Strong understanding of statistical modeling, predictive analytics, and mathematical optimization techniques.
Proficiency in Python, PySpark, and SQL, with hands‑on experience using data analysis and machine learning libraries.
Preferred Skills
Experience with mathematical optimization solvers such as Gurobi, CPLEX, Xpress MP, or Google OR‑Tools.
Proven ability to apply mathematical and analytical models to real‑world business scenarios.
Strong communication and presentation skills, capable of explaining complex concepts to business stakeholders.
Experience working with retail or CPG supply chain systems is highly desirable.
Seniority level:
Mid‑Senior level
Employment type:
Full‑time
Job function:
Engineering and Information Technology
Industries:
IT Services and IT Consulting
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Data Scientist
Location:
Omaha, Nebraska
Experience Required:
12+ Years
Key Responsibilities
Refactor and enhance existing optimization algorithms written in Python using object‑oriented programming principles.
Apply advanced data science techniques to solve business problems in supply chain optimization and retail/CPG inventory planning.
Analyze large and complex datasets using statistical methods and machine learning models to generate insights for replenishment and inventory allocation.
Develop, deploy, and maintain predictive models and optimization algorithms to improve inventory management, reduce stockouts, and optimize resource utilization.
Collaborate with cross‑functional teams to translate business requirements into scalable, data‑driven solutions.
Design and execute experiments to assess the effectiveness of replenishment strategies and allocation policies.
Monitor key supply chain performance metrics, evaluate model performance, and make recommendations for continuous improvement.
Stay updated on industry trends, tools, and best practices in data science, optimization, and supply chain management.
Mentor and collaborate with other data scientists to promote knowledge sharing and skill development.
Qualifications
Minimum 12+ years of professional experience as a Data Scientist, ideally within supply chain optimization or inventory allocation.
Master's or Ph.D. in Computer Science, Operations Research, Applied Mathematics, Machine Learning, or a related discipline.
Strong understanding of statistical modeling, predictive analytics, and mathematical optimization techniques.
Proficiency in Python, PySpark, and SQL, with hands‑on experience using data analysis and machine learning libraries.
Preferred Skills
Experience with mathematical optimization solvers such as Gurobi, CPLEX, Xpress MP, or Google OR‑Tools.
Proven ability to apply mathematical and analytical models to real‑world business scenarios.
Strong communication and presentation skills, capable of explaining complex concepts to business stakeholders.
Experience working with retail or CPG supply chain systems is highly desirable.
Seniority level:
Mid‑Senior level
Employment type:
Full‑time
Job function:
Engineering and Information Technology
Industries:
IT Services and IT Consulting
#J-18808-Ljbffr