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Model Predictive Control Jobs in Minnesota (NOW HIRING)

Senior Data Scientist

Virginia, MN · On-site

$131.30 - $237.35/hr

Apply cutting-edge techniques in statistical analysis, predictive analytics, entity resolution ... Familiarity with version control tools (git, svn, JIRA) and deployment technologies (Docker ...

Data Scientist

Virginia, MN · On-site

$95 - $130/hr

... predictive models. Additionally, candidate should be capable of leading and mentoring more junior ... Knowledge of CI/CD pipelines, version control (Git), and Infrastructure-as-Code. * Familiarity with ...

AD&D Advanced Software Engineer Sr

Duluth, MN · On-site

$113.22 - $160.11/hr

... learning model training.Experience in aviation-certified software is a plus, but candidates ... control systems. * Develop AI/ML algorithms for perception, decision-making, and predictive ...

AI Solutions Engineering Delivery Lead

Minneapolis, MN · On-site

$107K - $140K/yr

You will work on developing predictive models, conducting statistical analysis, and creating data ... control and continuous improvement of AI solutions, closely collaborating with business ...

Showing results 41-60

Model Predictive Control information

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 the typical challenges faced by engineers working with model predictive control 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 are the key skills and qualifications needed to thrive as a model predictive control 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.
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Infographic showing various Model Predictive Control job openings in Minnesota as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

Gift and Data Integrity Senior Specialist

Augsburg University

Minneapolis, MN

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 18 days ago


Job description

Company Description

Augsburg University has maintained a strong academic reputation defined by excellence in the liberal arts and professional studies since 1869. A welcoming campus in the heart of Minneapolis, Augsburg offers undergraduate and graduate degrees to nearly 3,200 diverse students.

Augsburg's mission is to educate students to be informed citizens, thoughtful stewards, critical thinkers, and responsible leaders. The Augsburg experience is supported by an engaged community that is committed to intentional diversity in its life and work. An Augsburg education is defined by excellence in the liberal arts and professional studies, guided by the faith and values of the Lutheran church, and shaped by its urban and global settings.

Augsburg invites individuals who share our mission and commitment to intentional diversity, equity, inclusion and belonging to join our community.  In particular, Augsburg invites BIPOC, LGBTQIA+, individuals with disabilities, women, veterans and those from underrepresented or marginalized backgrounds are encouraged to apply. 

Job Description

Summary of Position

The Gift and Data Integrity Senior Specialist plays a critical role in advancing Augsburg University's fundraising goals by ensuring the integrity, security, and strategic use of the institutional advancement database. As a key member of the Advancement Services team, this position oversees the end-to-end gift processing lifecycle, ensuring complex donations are accurately recorded in compliance with legal, IRS, and CASE standards. In addition to managing daily gift operations, the Senior Specialist partners with leadership to leverage statistical analysis for predictive annual giving reports, supports the implementation and onboarding of AI and automation tools, and serves as a technical resource and educator across the division. 

Primary Responsibilities

 Data Architecture, Gift Processing & Compliance 

  • Records: Conceptualize, structure, and govern fund, gift, and donor records. Exercise a high level of independent judgment and absolute discretion when managing sensitive constituent profiles, high-net-worth donor information, and complex philanthropic intents.
  • High-Level Gift Management: Accurately audit and record all donations into the university's fundraising database (Raiser's Edge), ensuring complex split-fund, recurring gifts, stock transfers, and pledges are captured.
  • Complex Ledger Maintenance: Manage recurring gift programs, structural pledge reminders, and track nuanced administrative details regarding Augsburg-owned insurance policies.
  • Compliance & Receipting: Interpret and apply IRS regulations, CASE guidelines, and institutional policies to generate legally compliant tax receipts and design strategic donor acknowledgment frameworks.
  • Information Governance: Formulate and maintain strict documentation standards for transactions and gift agreements. Serve as the primary authority on data integrity, providing intellectual oversight, policy training, and quality control supervision over tasks executed by auxiliary staff and student workers. 

Gift Analytics & Statistical Analysis 

  • Predictive Reporting Infrastructure: Partner collaboratively with the Director of Advancement Services and the Giving team to conceptualize, design, and build out a suite of data-driven reports. Then execute those reports on a regular schedule. Review and refresh reports annually to support the evolution of the fundraising strategy. Some reports will be spearheaded by the Gift and Data Integrity Senior Specialist and for other reports they will participate in data hygiene. 
  • Statistical Insights: Utilize data models to track alumni giving trends, donor retention behaviors to directly inform fundraising strategies.
  • Data Hygiene Auditing: Autonomously build and deploy complex queries and data exports to conduct gift data health audits, maintaining supreme data hygiene and compliance. 

Systems Innovation & Emerging Technology Implementation

  • Systems Optimization & Automation Design: Research, engineer, and deploy advanced workflow automations to maximize operational efficiency, reduce manual friction, and scale gift-entry paradigms.
  • AI Tool Integration: Participate in exploration, onboarding, deployment, testing and use of emerging technical integrations, such as the Blackbaud Development Agent.
  • Cross-Functional Support: Provide advanced technical insight to campus partners and Institutional Advancement teams (Major Gifts, Annual Giving, Alumni Relations) to support coordinated, multi-channel fundraising campaigns and high-stakes events.

Technical Training & Collaborative Leadership

  • Internal Teaching & Onboarding: Design training workflows and lead educational sessions to teach advancement colleagues and campus partners how to successfully leverage CRM tools, dashboards, and system updates.
  • Constituent Relations: Serve as an expert point of contact for internal staff, division leadership, and external supporters regarding giving histories, event registration tracking (e.g., Homecoming, Galas), and complex giving procedures.

Work Environment and Physical Demands

  • Typical work environment is an office. Sedentary work for long periods of time. 
  • Regular computer and phone use. 
  • Occasional work on evenings or weekends for events is expected.
  • Optional hybrid work schedule: in-office four (4) days per week and remote work one (1) day per week.
Qualifications

Minimum Qualifications

  • Bachelor's degree (a degree in Statistics, Mathematics, Data Analytics, or a related field is highly preferred). 
  • Minimum of three (3) to four (4) years of directly related professional experience.
  • Proven technical proficiency and hands-on experience working with Raiser's Edge or a comparable enterprise-level CRM.
  • Highly proficient with Microsoft Office Suite (Word, Excel, and PowerPoint).
  • Proficient in Google Suite (Mail, Calendar, Drive, and Docs).

Preferred Qualifications

  • Prior experience in a higher education institutional advancement setting.
  • Demonstrated experience optimizing database processes using data integration software (e.g., Omatic).
  • Experience or strong academic background in statistical modeling, reporting, and data visualization.

Knowledge, Skills, Abilities

  • Ability to work effectively in a diverse work environment.
  • Outstanding organizational skills, accuracy, and attention to detail. 
  • Collaborative style with the ability to work independently or with little supervision. 
  • Proactive self-starter and proven ability in taking initiative.
  • Ability to successfully prioritize and manage multiple projects with differing timelines.
  • Ability to lead and teach others.
  • Committed to maintaining strict confidentiality
Additional Information

Application Requirements

To be considered for this position please include the following in your application:

  • Resume (required)

Compensation & Benefits at Augsburg

  • The compensation range is $50,000 - $55,000 annually, DOQ. 

Augsburg University offers a competitive and comprehensive total rewards program including:

  • Medical, dental and vision coverage
  • A generous 403(b) matching program with an employer contributions of up to 8% upon eligibility
  • Up to 100% tuition remission for employees, spouses and dependents, and participation in the Tuition Exchange program with colleges and universities throughout the US
  • Generous paid time-off, including 14 paid holidays, 12 sick days, 2 community service days, and vacation of up to 22 days per year immediately upon hire
  • Employer-paid STD, LTD and life insurance
  • Employee Assistance Program (EAP) for all employees

Equal Opportunity Statement

Augsburg is an equal opportunity employer and does not discriminate on the basis of gender, sexual orientation, marital status, gender identity, race, age, disability, religion, national origin, color, or any other protected class.  

Augsburg University is committed to providing equal employment opportunity to all applicants and employees regardless of their race, color, creed, religion, gender, age, national origin, familial status, disability, veteran status, sexual orientation, gender identity, gender expression, marital status or public assistance status, or any other characteristic protected by federal, state, or local law. 

If you need a reasonable accommodation to complete our application process, please contact our Human Resources Department at phone number: 612-330-1058 or email: [email protected].