- Develop and implement mathematical models and algorithms to solve complex business problems.
- Utilize optimization techniques such as linear programming, integer programming, and dynamic programming.
- Develop and apply simulation models.
- Develop and refine optimization models that enhance efficiency and effectiveness, influencing critical business decisions and supporting the strategic objectives of the Trailblazer initiative.
- Collaborate with business units to understand their challenges and develop quantitative solutions that integrate seamlessly with their operations.
- Conduct deep analyses of large datasets to discover trends and efficiencies, driving continuous improvements and innovations in business practices.
- Continuously improve existing models by incorporating new data sources and updating methodologies based on the latest research and techniques.
- Present complex model findings and strategic recommendations to senior management, ensuring alignment and informed decision-making.
- Design models that are not only effective but also scalable and adaptable, preparing the organization for future challenges and opportunities.
- Bachelor's degree in a related discipline and 4 years' experience in a related field. The right candidate could also have a different combination, such as a master's degree and 2 years' experience; a Ph.D. and up to 1 year of experience; or 8 years' experience in a related field
- Experience developing and implementing large scale optimization models using Linear programming, Mixed Integer programming and heuristics
- Strong background in utilizing optimization libraries such as CPLEX or Gurobi for solving large-scale linear and non-linear optimization problems.
- Experience with integrating Machine Learning algorithms into decision-support tools is a plus.
- Proficiency in Python, R, or other analytics platforms, with a strong background in data manipulation and statistical analysis.
- Proficiency in programming languages like Python, C++ and build automation
- Experience in automotive supply chain a plus
- Knowledge of Operations Research techniques and mathematical modeling for supply chain optimization.
- Extensive experience in developing and implementing optimization algorithms for transportation planning or similar domains.
- Certification in relevant data science or analytics platforms is highly desirable.
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Data Scientist - Crockett, United States - Vaco
Description
***Data Scientist - Model Optimization***
Find out if this opportunity is a good fit by reading all of the information that follows below.***Onsite in Houston, TX***
About the job:
The Data Scientist - Model Optimization plays a pivotal role in advancing the company's digital transformation. In this role, you will be responsible for developing and implementing mathematical models and algorithms to solve complex business problems. You should have a passion for mathematical problem solving. The ideal candidate will have a strong background in operations research, mathematics, and/or computer science. You should have experience with optimization techniques, such as linear programming, integer programming, and dynamic programming, as well as experience with developing and applying simulation models. Additionally, you should have strong analytical and problem-solving skills.
Responsibilities:
Qualifications: