Data Scientist

Texas Instruments•Richardson, TX

About The Position

We are seeking a distinguished professional to join our Smart Manufacturing and Automation team as an Operations Research Lead. As a leading expert in the field, you will be responsible for developing and implementing cutting-edge mathematical models and algorithms to optimize production planning, scheduling, and resource allocation.

Requirements

Ph.D. in Operations Research, Mathematics, Computer Science, or related field
10+ years of experience in operations research, mathematical optimization, or related field, with a strong track record of innovation and achievement

Nice To Haves

Recognized expert in the field, with a strong reputation and network in the academic and industry communities
Proven track record of developing and implementing optimization solutions that have resulted in significant improvements in efficiency, cost reduction, and productivity
Hands-on experience with shop floor operations and a deep understanding of manufacturing systems and processes
Proficiency in optimization software (CPLEX or Gurobi), programming languages (Python, R, or SQL), and machine learning libraries (Scikit-learn or TensorFlow)
Strong analytical and problem-solving skills, with the ability to communicate complex technical concepts to non-technical stakeholders
Excellent leadership and collaboration skills, with experience in leading cross-functional teams to implement optimization solutions
A strong publication record, with numerous academic papers and patents in the field of operations research and optimization
Industry recognition, with awards or honors for contributions to the field of operations research and optimization

Responsibilities

Develop and implement advanced mathematical models and algorithms to optimize production planning, scheduling, and resource allocation
Select algorithm approaches and techniques to solve complex optimization problems
Choose commercial and open-source tools and standardize model development
Architect optimization solutions with factory systems and business process integration
Develop and implement mathematical programming or artificial intelligence-based algorithms to optimize production plans and schedules
Lead the path to AI-based scheduling and optimization
Analyze data to identify trends and opportunities for improvement
Develop and implement machine learning models to predict production outcomes

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