What are the responsibilities and job description for the Operations Research Engineer, Mid-Level position at Jobright?
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Job Summary:
EverDriven is a rapidly growing, tech-enabled transportation management company dedicated to providing safe and efficient transportation for children with special needs. They are seeking a highly skilled Operations Research Engineer to design and develop optimization models for student transportation, directly impacting safety and operational efficiency.
Responsibilities:
• Model & Algorithm Development: Design, build, and implement advanced optimization models for various VRP contexts, including Capacitated VRP (CVRP), VRP with Time Windows (VRPTW), and dynamic routing scenarios.
• Heuristics & Solvers: Develop and refine custom heuristics and metaheuristics (e.g., Tabu Search, Genetic Algorithms) to find high-quality solutions for large-scale, real-world problems. Utilize commercial and open-source solvers (e.g., Gurobi, CPLEX, Google OR-Tools).
• Data Analysis & Simulation: Analyze historical and real-time data—including student locations, school bell times, traffic patterns, and vehicle telematics—to inform model parameters and constraints. Build simulation frameworks to test and validate model performance before deployment.
• Predictive Modeling: Build and deploy machine learning models to support the routing engine, focusing on areas like travel time estimation (ETAs), demand forecasting, and anomaly detection.
• Cloud-based Data Science - Standing up and working in cloud-based data science environments.
• MLOps & Model Lifecycle Management: Own the end-to-end lifecycle of predictive models, including automated deployment, performance monitoring, drift detection, and continuous retraining to ensure accuracy and reliability in a live production environment.
• Production Implementation: Write robust, production-ready Python code to integrate your optimization and ML models into our live operational platform. Work closely with software engineers to expose your models via APIs.
• Performance Measurement: Define and monitor key performance indicators (KPIs) such as on-time performance, ride duration, vehicle utilization, and cost-per-student. Continuously iterate on models to drive improvements.
• Strategic Collaboration: Partner with product, operations, and engineering teams to understand business constraints and translate them into mathematical models. Clearly communicate complex findings and recommendations to both technical and non-technical stakeholders.
Qualifications:
Required:
• Master's degree or PhD in Operations Research, Industrial Engineering, Computer Science, Applied Mathematics, or a related quantitative field. (A Bachelor's degree with exceptional relevant experience will be considered).
• 3 years of professional experience in an operations research, data science, or quantitative role with a focus on optimization or machine learning.
• Deep theoretical and practical understanding of the Vehicle Routing Problem and its variants, and solution methodologies.
• Strong background in mathematical optimization, linear programming, statistical analysis, and combinatorial optimization.
• Proven experience building and implementing optimization or ML models in Python (or R with experience translating R to production-level Python code).
• Experience with open source data science toolkits including Python (numpy, pandas, scikit, PySpark) or R (Tidyverse/Tidymodels).
• Hands-on experience with at least one optimization solver (e.g., Gurobi, CPLEX, SCIP, Google OR-Tools).
• Familiarity with geospatial data and tools (e.g., PostGIS, GeoPandas, OSRM).
• Proficiency with data science and machine learning libraries (e.g., pandas, NumPy, scikit-learn, PyTorch).
• Strong software engineering practices (e.g., version control with Git, unit testing, CI/CD).
• Be able to translate models into software design functional requirements and specifications.
• Strong proficiency in SQL for data extraction and analysis.
Preferred:
• Experience in the logistics, transportation, or ride-sharing industry.
• Experience with dynamic or real-time routing algorithms.
• Big Data Technologies: Hands-on experience with distributed computing frameworks like Apache Spark or Dask.
• Experience with implementing MLOps practices using MLOps tools and platforms (e.g., MLflow, Kubeflow, Docker, Kubernetes, or cloud equivalents like Azure Machine Learning or Amazon SageMaker).
• Development experience with back-end software services. Preferably with Microsoft .Net.
Company:
EverDriven is a contracted alternative transportation company focused exclusively on providing solutions to student transportation needs. Founded in 2005, the company is headquartered in Greenwood Village, Colorado, USA, with a team of employees. The company is currently Growth Stage.
Salary : $125,000 - $175,000
