Job Description
Operations Research Scientist
Environment: Hybrid-each Week-2 days onsite
Location: Atlanta, GA 30308
Client Corporation is seeking an innovative and highly analytical Operations Research Scientist to develop advanced optimization, machine learning, and decision-support solutions that improve network performance, increase operational efficiency, enhance service reliability, and reduce costs.
This role leverages cutting-edge operations research methodologies, reinforcement learning, artificial intelligence, and mathematical optimization to solve complex transportation and logistics challenges. The successful candidate will work closely with business stakeholders, software engineers, and operational leaders to transform data into actionable insights and scalable decision-support systems.
Education
Experience Required:
Environment: Hybrid-each Week-2 days onsite
Location: Atlanta, GA 30308
Client Corporation is seeking an innovative and highly analytical Operations Research Scientist to develop advanced optimization, machine learning, and decision-support solutions that improve network performance, increase operational efficiency, enhance service reliability, and reduce costs.
This role leverages cutting-edge operations research methodologies, reinforcement learning, artificial intelligence, and mathematical optimization to solve complex transportation and logistics challenges. The successful candidate will work closely with business stakeholders, software engineers, and operational leaders to transform data into actionable insights and scalable decision-support systems.
Education
- Master's or Ph.D. degree in:
- Operations Research
- Industrial Engineering
- Applied Mathematics
- Statistics
- Computer Science
- Information Systems
- Data Science
- Other related quantitative disciplines
Experience Required:
- 3-5 years of experience developing and deploying decision-support systems using operations research methodologies.
- 3-5 years of experience supporting network recovery, disruption management, and operational resiliency initiatives.
- 3-5 years of experience designing and implementing optimization models for large-scale operational planning and real-time decision-making applications.
- 3-5 years of experience applying reinforcement learning, machine learning, and network optimization techniques to support adaptive and autonomous decision-making.
- Experience developing nonlinear optimization and AI-enhanced optimization models that improve solution quality, robustness, scalability, and explainability.
- 3-5 years of experience following software development best practices, including design, testing, deployment, and maintenance of production applications.
- Knowledge of railroad operations, transportation planning, and network design principles.
- Experience with train scheduling, routing, blocking, crew planning, or asset utilization optimization.
- Experience measuring, analyzing, and improving transportation service performance.
- Experience developing real-time analytics and decision-support systems for large-scale logistics or transportation networks.
- Strong expertise in mathematical optimization techniques, including Linear Programming (LP), Mixed Integer Programming (MIP), and Nonlinear Optimization (NLP)
- Experience with commercial or open-source optimization solvers such as Gurobi or CPLEX
- Experience with machine learning, predictive analytics, neural networks, deep learning, or discrete-event simulation.
- Proficiency in Python and experience with one or more additional programming languages such as Java or C++.
- Experience with model deployment and production integration.
- Strong SQL skills and experience working with large-scale relational databases.
- Experience with data quality assessment, feature engineering, and model validation.
- Develop real-time, tactical, and strategic network disruption management and recovery models to support railroad operations and service resiliency.
- Provide production support, maintenance, and continuous enhancements for existing operations research applications.
- Design, develop, and implement advanced mathematical optimization, simulation, and machine learning models using Python, Java or C++.
- Evaluate the accuracy, completeness, and quality of data sources, and develop effective solutions to address data quality issues and gaps.
- Collaborate with business partners across multiple departments to identify opportunities for operational improvements and process optimization.
- Work closely with application development teams to integrate analytical models and decision-support tools into production environments.
- Provide technical leadership and supervise team members to achieve organizational goals by fostering collaboration, open communication, professional development, and adaptability.
- Communicate analytical findings, model recommendations, and business impacts to stakeholders and senior leadership to support data-driven decision-making.
- Lead initiatives focused on improving network resilience, service reliability, and operational recovery during planned and unplanned disruptions.
Numbers & Facts
| Location | Atlanta, GA |
| Industry | Staffing/Employment Agencies |
| Company Size | 50 to 99 employees |
| Year Founded | 2014 |
| Website | http://www.insyncstaffing.com/default.html |
About Company
We recognize the VMS program management team is our customer and needs to be serviced with integrity, so we built and continue to improve upon our delivery methods as we strive to provide the highest quality service possible.
inSync Staffing’s management team recognized ten years ago the inevitable changes to the staffing industry being brought about by technology and the growing trend of Fortune 1000 corporations to outsource management of their contingent workforces to meet compliance and cost control goals. Rather than swim upstream against the changes, inSync Staffing has embraced MSP and VMS programs as our customers, not competitors. We asked program managers how they want to be serviced.
The result of their input is that we have structured inSync Staffing as a recruiting and customer service organization, unlike traditional staffing companies who sell directly to the end client. Our delivery model allows us concentrates our resources on how to best supply candidates in a very competitive MSP/VMS program environment.
Skills
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