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Remote Embedded Machine Learning Jobs in Minnesota

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Remote Embedded Machine Learning information

What are the key skills and qualifications needed to thrive as a Remote Embedded Machine Learning Engineer, and why are they important?

To thrive as a Remote Embedded Machine Learning Engineer, you need a solid background in embedded systems, machine learning algorithms, and programming languages like C/C++ and Python, often supported by a degree in computer science, electrical engineering, or related fields. Familiarity with microcontrollers, edge AI frameworks (such as TensorFlow Lite or Edge Impulse), and version control systems is typically required. Strong problem-solving skills, effective communication, and self-motivation are essential soft skills for collaborating remotely and troubleshooting complex issues. These skills ensure successful deployment of intelligent solutions on resource-constrained devices and effective teamwork in distributed environments.

What are some common challenges faced by Remote Embedded Machine Learning Engineers, and how can they be addressed?

Remote Embedded Machine Learning Engineers often encounter challenges related to hardware access, debugging embedded devices remotely, and collaborating with cross-functional teams across time zones. To address these, it's important to set up robust remote development environments, use simulation tools when physical hardware isn't available, and establish clear communication channels for effective teamwork. Regular virtual meetings and detailed documentation also help ensure alignment and smooth progress, despite the remote nature of the work.

What is a Remote Embedded Machine Learning Engineer?

A Remote Embedded Machine Learning Engineer is a professional who develops and deploys machine learning models on embedded systems like microcontrollers, IoT devices, and edge hardware, all while working remotely. Their work involves optimizing algorithms to run efficiently on devices with limited computing power, memory, and battery life. These engineers typically use frameworks such as TensorFlow Lite or TinyML to design intelligent features that operate directly on hardware, enabling real-time decision-making without relying heavily on cloud connectivity. They collaborate with cross-functional teams and often troubleshoot both software and hardware issues from a remote location.

What is the difference between Remote Embedded Machine Learning vs Remote Data Scientist?

AspectRemote Embedded Machine LearningRemote Data Scientist
Required CredentialsBachelor's or Master's in Computer Science, Electrical Engineering, or related fields; experience with embedded systems and ML frameworksBachelor's or Master's in Data Science, Statistics, or related fields; proficiency in data analysis and ML algorithms
Work EnvironmentEmbedded hardware devices, IoT systems, real-time processing environmentsCloud platforms, data analysis labs, remote offices
Employer & Industry UsageTech companies, IoT device manufacturers, automotive, roboticsFinance, healthcare, marketing, tech firms

Remote Embedded Machine Learning specialists focus on integrating ML models into embedded hardware for real-time applications, often working with IoT and robotics. In contrast, Remote Data Scientists analyze large datasets to extract insights, primarily working in cloud or office environments. Both roles require strong analytical skills but differ in technical focus and work settings.

What are the most commonly searched types of Embedded Machine Learning jobs in Minnesota? The most popular types of Embedded Machine Learning jobs in Minnesota are:
What are popular job titles related to Remote Embedded Machine Learning jobs in Minnesota? For Remote Embedded Machine Learning jobs in Minnesota, the most frequently searched job titles are:
What job categories do people searching Remote Embedded Machine Learning jobs in Minnesota look for? The top searched job categories for Remote Embedded Machine Learning jobs in Minnesota are:
What cities in Minnesota are hiring for Remote Embedded Machine Learning jobs? Cities in Minnesota with the most Remote Embedded Machine Learning job openings:
Senior Director, Data Science - NextGen Forecasting - Remote

Senior Director, Data Science - NextGen Forecasting - Remote

UnitedHealth Group

Minnetonka, MN • On-site, Remote

Full-time

Retirement

Posted 16 days ago


UnitedHealth Group rating

7.5

Company rating: 7.5 out of 10

Based on 140 frontline employees who took The Breakroom Quiz

219th of 865 rated healthcare providers


Job description

Optum Tech is a global leader in health care innovation. Our teams develop cutting-edge solutions that help people live healthier lives and help make the health system work better for everyone. From advanced data analytics and AI to cybersecurity, we use innovative approaches to solve some of health care's most complex challenges. Your contributions here have the potential to change lives. Ready to build the next breakthrough? Join us to start Caring. Connecting. Growing together.


The health solutions marketplace is hungry for new ideas, innovative products and software that drives elevated performance for the business and the customer. The UnitedHealth Group family of businesses is feeding incredible solutions to that marketplace every day by bringing out the best in our software engineering teams. We serve customers across the health system. Not only do we have more of them every day, we also have more technology, greater data resources and far broader expertise than any competitor anywhere. We're out to change the way our businesses and consumers engage with technology. If you're in, you'll be challenged like never before. It's time to join this history making.


You'll enjoy the flexibility to work remotely * from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week.


Primary Responsibilities:

  • Provide enterprise level leadership for advanced forecasting, predictive, and prescriptive analytics supporting strategic, operational, and financial decision making
  • Lead the design, execution, and scaling of next generation forecasting capabilities leveraging complex, unstructured, and high volume datasets
  • Apply advanced statistical modeling, machine learning, simulation, optimization, and mathematical techniques to deliver materially earlier insight into emerging trends and risks
  • Translate complex and ambiguous business questions into analytically rigorous, scalable forecasting solutions delivering measurable enterprise value
  • Provide strategic direction and accountability for forecasting architecture, modeling strategy, prioritization, validation, and deployment across the Next Gen Forecasting program
  • Direct multiple layers of management and senior level data science professionals, ensuring strong technical rigor, delivery discipline, and talent development
  • Establish forecasting standards, governance, and validation frameworks ensuring accuracy, interpretability, scalability, and sustained stakeholder trust
  • Partner closely with Finance, Actuarial, Healthcare Economics, and Technology leaders to align forecasting roadmaps, manage cross functional dependencies, and embed insights into enterprise decision workflows
  • Design and operationalize advanced time series forecasting solutions using classical statistical methods (ARIMA/SARIMA, ETS, state space models) as well as modern machine learning and deep learning approaches
  • Lead development of forecasting frameworks that explicitly account for trend, seasonality, stationarity, autocorrelation, and temporal dependencies across large scale enterprise datasets
  • Establish enterprise forecasting standards including backtesting methodologies, rolling/expanding window validation, probabilistic forecasting, prediction interval generation, and analytical risk management practices
  • Drive advanced feature engineering strategies for time series forecasting, including lag features, rolling statistics, calendar effects, Fourier terms, and incorporation of exogenous variables such as events, holidays, and external business drivers
  • Lead implementation of multi-step forecasting strategies including recursive, direct, and hybrid approaches, leveraging sequence modeling architectures such as LSTM and Transformer-based forecasting models where appropriate
  • Ensure forecasting solutions appropriately address time-based validation, temporal data leakage prevention, model interpretability, scalability, and sustained stakeholder trust


You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in. 
 

Required Qualifications:

  • Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, or related field
  • 15 Years of overall experience in data science, forecasting, predictive, and prescriptive analytics at enterprise scale
  • Proven experience leading multi layer data science organizations or highly complex analytics programs
  • Deep expertise in time series forecasting, statistics, machine learning, simulation, optimization, and advanced mathematical techniques
  • Hands-on experience with forecasting methodologies including ARIMA/SARIMA, exponential smoothing (ETS), state space models, and machine learning based forecasting approaches
  • Demonstrated expertise in handling non-stationary time series data, seasonality decomposition, trend modeling, temporal feature engineering, and forecasting validation methodologies
  • Experience applying machine learning techniques (e.g., XGBoost, LightGBM) to forecasting problems including lag-based feature engineering, rolling window statistics, and proper handling of temporal dependencies
  • Solid understanding of forecasting evaluation metrics and validation approaches including MAE, RMSE, MAPE, rolling window validation, and backtesting frameworks
  • Demonstrated ability to drive analytically rigorous solutions that influence strategic, operational, and financial decision making
  • Exposure to Gen AI skill - Large Language Model, RAG


Preferred Qualifications:  

  • Master's or PhD in Data Science, Statistics, Applied Mathematics, Operations Research, or related discipline
  • Experience in healthcare, actuarial, or healthcare economics analytics environments
  • Experience leading high visibility, enterprise scale AI or advanced forecasting programs
  • Experience using advanced analytics platforms and tools including SQL, Python, R, Hadoop, and large scale data technologies
  • Experience with advanced forecasting frameworks and libraries such as Prophet, statsmodels, darts, Nixtla, scikit-learn, TensorFlow, or PyTorch
  • Solid background in forecasting governance, validation, and analytical risk management, and probabilistic forecasting methodologies
  • Familiarity with sequence-to-sequence forecasting architectures, Transformer models, and modern deep learning approaches for time series forecasting

*All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy.


Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $159,300 to $273,200 annually based on full-time employment. We comply with all minimum wage laws as applicable.

Application Deadline: This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants.


At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.


UnitedHealth Group is an Equal Employment Opportunity employer under applicable law and qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations.


UnitedHealth Group is a drug - free workplace. Candidates are required to pass a drug test before beginning employment. 


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