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Model Predictive Control Jobs in Kentucky (NOW HIRING)

Grading and drainage design and stormwater modeling experience. * * Erosion and sediment control ... predictive models, spreadsheets, and tools. * Demonstrated commitment to safety, ethical ...

Grading and drainage design and stormwater modeling experience. * * Erosion and sediment control ... predictive models, spreadsheets, and tools. * Demonstrated commitment to safety, ethical decision ...

Traffic Engineer

Louisville, KY · On-site

$83.60K - $113.90K/yr

... modeling and forecasting, corridor planning, traffic signal operations, signal and ITS design ... Prepare designs of traffic control devices and systems, including traffic signals, signing ...

Cyber Manager - ServiceNow

Louisville, KY · On-site +1

$106.70K - $144.10K/yr

... control, and status reporting with clear key performance indicators, value realization, and ... Orchestrating cross-functional teams and vendors across onshore and offshore models; aligning ...

Promote company mission, vision, and core values while modeling continuous improvement. * Develop ... Manage preventive, predictive, and corrective maintenance programs across foundry operations.

Promote company mission, vision, and core values while modeling continuous improvement. * Develop ... Manage preventive, predictive, and corrective maintenance programs across foundry operations.

Model Predictive Control information

What are the key skills and qualifications needed to thrive as a Model Predictive Control (MPC) Engineer, and why are they important?

To thrive as a Model Predictive Control Engineer, you need strong foundations in control theory, applied mathematics, and process engineering, usually supported by a degree in engineering or a related field. Proficiency with simulation tools such as MATLAB/Simulink, programming languages like Python or C++, and familiarity with industrial automation systems are typically required. Analytical thinking, problem-solving abilities, and effective communication skills help distinguish top performers in this role. These skills are essential for designing, implementing, and optimizing advanced control algorithms that improve system performance and reliability in complex industrial environments.

What are the typical challenges faced by engineers working with Model Predictive Control (MPC) systems in an industrial setting?

Engineers working with Model Predictive Control systems often encounter challenges related to model accuracy, computational demands, and real-time implementation. Ensuring the process model accurately represents the plant dynamics is critical, as discrepancies can lead to suboptimal control performance. Additionally, MPC algorithms can be computationally intensive, particularly for large-scale or fast processes, requiring careful tuning and optimization to maintain real-time operation. Collaboration with process engineers and IT specialists is common, as integrating MPC with existing control systems and plant infrastructure is a key part of the role.

What is Model Predictive Control?

Model Predictive Control (MPC) is an advanced method of process control that uses a mathematical model to predict and optimize the future behavior of a system. It works by solving an optimization problem at each control step to determine the best sequence of control actions, taking into account system constraints and objectives. MPC is widely used in industries such as chemical processing, energy, and automotive because it can handle multivariable control problems and anticipate future events. Its predictive nature allows for improved performance, stability, and efficiency compared to traditional control methods.

What is the difference between Model Predictive Control vs Control Systems Engineer?

AspectModel Predictive ControlControl Systems Engineer
CredentialsEngineering degree, control theory, process modelingEngineering degree, control systems, automation
Work EnvironmentIndustrial automation, process control, manufacturingDesign, develop, and maintain control systems across industries
Industry UsageProcess industries, chemical, oil & gas, manufacturingAutomation, robotics, embedded systems, industrial sectors

Model Predictive Control (MPC) focuses on advanced control algorithms for optimizing processes, while Control Systems Engineers design and implement various control systems. MPC is a specialized skill within control engineering, often requiring knowledge of process modeling and optimization, whereas Control Systems Engineers have broader responsibilities across multiple control technologies. Both roles are essential in industrial automation but differ in scope and application.

What are popular job titles related to Model Predictive Control jobs in Kentucky? For Model Predictive Control jobs in Kentucky, the most frequently searched job titles are:
What job categories do people searching Model Predictive Control jobs in Kentucky look for? The top searched job categories for Model Predictive Control jobs in Kentucky are:

Business Analyst - AI and Data Analytics

DHL Express (USA), Inc.

Erlanger, KY • On-site

Other

Medical, Dental, Vision, Life, Retirement, PTO

This job post has expired today. Applications are no longer accepted.


Job description

What makes DHL great? Our People! We know each employee's individual contributions make us the #1 Delivery and Logistics Company in the world.

Distinguished as No. 1 World's Best Workplace by Great Place to Work and Fortune Magazine

DHL is committed to maintaining an environment that empowers every team member to make the greatest possible impact on our business. Our culture is about personal commitment - to our business, to each other and to our global communities. DHL is dedicated to being a great place to work. In addition to competitive compensation packages, our employees enjoy a range of programs, services and benefits that bring the best to their personal lives.

Start YOUR career with DHL today...

We have an immediate career opportunity for a Business Analyst - AI and Data Analytics with a strong foundation in data analytics, AI-enabled insights, and process automation. This role will serve as a critical link between operations, trade compliance, customs brokerage, finance, and IT teams, driving the evolution of clearance processes through data-driven and AI-powered solutions. The position is responsible for analyzing, designing, and optimizing end-to-end clearance processes to ensure compliant, efficient, cost-effective, and timely import/export operations. The ideal candidate will leverage advanced analytics, machine learning models, and automation tools to identify opportunities, improve decision-making, and deliver strategic insights that support DHL's global logistics network and regulatory compliance objectives.


Key Responsibilities:

Data Analysis, Reporting & Insights

  • Analyze operational and financial data to support daily business decisions across DHL teams.
  • Track, enhance, and automate key performance indicators (KPIs) for clearance functions (e.g., clearance cycle times, delays, duty/tax forecasting, exception rates, non-compliance risks).
  • Develop and maintain interactive dashboards and self-service analytics using tools like Power BI.
  • Translate complex datasets into actionable insights for internal stakeholders including Operations, Compliance, and Gateway leadership.

AI, Predictive Analytics & Automation

  • Apply AI/ML techniques (e.g., classification, anomaly detection, time-series forecasting) to optimize clearance workflows and identify patterns not visible through traditional analytics.
  • Assist in building intelligent automation solutions (e.g., RPA, workflow automation) to streamline repetitive clearance and reporting processes.
  • Integrate predictive outputs into operational dashboards and business processes to enable real-time, data-driven decision-making.
  • Explore and support implementation of Generative AI use cases (e.g., automated report generation, document summarization, tariff classification assistance).

Data Engineering & Model Operations

  • Create and maintain data pipelines utilizing Python, SQL, and Snowflake to support analytics and AI use cases.
  • Ensure data quality, governance, reproducibility, and version control across all analytics and modeling workflows.
  • Monitor model performance (accuracy, drift, data quality) and assist in model retraining and tuning
  • Collaborate with IT and data engineering teams to scale and produce analytics solutions.

Process Improvement & Business Collaboration

  • Identify opportunities for process optimization, cost reduction, and service improvements within clearance operations.
  • Analyze service incidents and apply root cause analysis and AI-driven pattern detection to reduce recurring issues.
  • Support cross-functional projects aimed at enhancing compliance, efficiency, and customer experience.

Governance, Compliance & AI Ethics

  • Ensure adherence to DHL's data governance, privacy, and Responsible AI standards.
  • Maintain thorough documentation, model cards, and audit trails for all analytics and AI solutions.
  • Support compliance with global trade regulations by leveraging data insights and automated validation checks.

Skills & Qualifications:


  • 2-4 years of experience in data analytics, business analytics, or a related field.
  • Bachelor's degree in Business, Supply Chain, Logistics, Data Analytics, Finance, Computer Science, or equivalent experience.
  • Strong proficiency in Excel and data analysis concepts.
  • Working knowledge of Python, SQL, Snowflake for data manipulation and analysis.
  • Experience with data visualization tools (e.g., Power BI).
  • Ability to analyze data, identify trends, and communicate insights clearly to business stakeholders.
  • Knowledge of Generative AI tools and applications within business workflows.
  • Attention to detail and ability to manage multiple tasks with guidance.
  • Interest in learning customs, trade, and logistics processes.
  • This position requires access to secured airport areas. Selected candidates must be able to obtain and maintain a Security Identification Display Area (SIDA) badge, which includes passing a criminal history records check, fingerprinting, and meeting all federal, state, and local regulatory requirements. Candidates must be able to provide all documentation necessary to support the badging process.

Employee Benefits & Incentives 


DHL Express benefits and incentive offerings are designed to reflect a substantial experience for both employees and their dependents during their career and life journey. The specifics will vary, but wherever you join and in whatever role, you'll find our benefits and rewards are among the best in the industry. They include:

  • Competitive Pay
  • Retirement Savings - 401K with company match 
  • Medical, Dental, Vision, well-being programs 
  • Tuition Reimbursement 
  • Generous Paid Time Off
  • Paid Leave
  • Employee Discount Program 
  • Employee Assistance & Work Life Program 
  • Outstanding training opportunities 

DHL is an equal opportunity employer.  We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other protected characteristic.  The EEO is the Law poster is available here: https://www.eeoc.gov/employers/eeo-law-poster 

  

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.