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Remote Aws Machine Learning Jobs in Michigan (NOW HIRING)

Senior Data Analyst

Detroit, MI · On-site +1

$96K - $132K/yr

Lead the design, development, and implementation of advanced machine learning models and algorithms ... Familiarity with cloud computing platforms like AWS, Azure, or Google Cloud. * Experience where ...

Practice Manager - AI & Data

Troy, MI · On-site +1

$160K - $190K/yr

Cloud-based AI architectures (AWS, Azure, GCP AI services) * Machine Learning & Deep Learning ... REMOTE/HYBRID AND/OR CALIFORNIA, COLORADO, MARYLAND, CONNECTICUT, ILLINOIS, MINNESOTA, VERMONT ...

Analytics Scientist

Dearborn, MI · On-site +1

$130K - $169K/yr

... Machine Learning Model Development to support business decisions in credit risk analysis. We are ... GCP and AWS) to conduct model development. 2. Researching and adapting new python algorithm ...

Remote micro1 is engaging PhD-level Engineers in Electrical, Mechanical, or Chemical disciplines to ... Experience with or interest in AI, machine learning, or technology-driven projects (a plus, not ...

Remote micro1 is engaging PhD-level Engineers in Electrical, Mechanical, or Chemical disciplines to ... Experience with or interest in AI, machine learning, or technology-driven projects (a plus, not ...

Software Architect

Novi, MI · On-site +1

$143K - $256K/yr

... and AWS-based server-side infrastructure Minimum Qualifications * Bachelor's degree in computer ... Working knowledge of LLMs and machine learning, with an understanding of key concepts and hands-on ...

Our AI solutions incorporate applications across the AI and machine learning spectrum, including ... OneStream is an Equal Opportunity Employer. #LI-REMOTE #LI-JP1

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Remote Aws Machine Learning information

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

To thrive as a Remote AWS Machine Learning Engineer, you need a strong background in machine learning algorithms, statistical analysis, and proficiency in programming languages such as Python, often supported by a relevant degree or certification. Familiarity with AWS services like SageMaker, Lambda, and EC2, as well as experience using cloud-based ML tools and AWS Certified Machine Learning credentials, is typically required. Excellent problem-solving skills, self-motivation, and clear written communication are valuable soft skills for remote collaboration and project management. These skills ensure effective model development, seamless deployment on cloud infrastructure, and successful remote teamwork in delivering scalable ML solutions.

What are remote AWS Machine Learning jobs?

Remote AWS Machine Learning jobs involve working with Amazon Web Services' suite of machine learning tools and services, such as SageMaker, to build, train, and deploy machine learning models. These positions allow professionals to work from anywhere, collaborating with teams virtually while leveraging AWS infrastructure to solve data-driven problems. Responsibilities often include data preprocessing, model development, and deploying scalable solutions in the cloud. Typical job titles may include Machine Learning Engineer, Data Scientist, or AI Developer, all with a focus on AWS technologies. These roles require strong programming skills, experience with cloud computing, and a background in machine learning or data science.

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

AspectRemote Aws Machine LearningRemote Data Scientist
Required CredentialsAWS certifications, machine learning coursesStatistics, data analysis, programming skills
Work EnvironmentCloud platforms, AWS services, remote teamsData analysis, modeling, research in remote settings
Industry UsageTech, finance, healthcare using AWS ML toolsResearch, consulting, analytics across industries

Remote AWS Machine Learning specialists focus on deploying machine learning models using AWS cloud services, requiring AWS certifications and cloud expertise. Remote Data Scientists analyze data, build models, and interpret results, often with a stronger emphasis on statistics and programming. While both roles work remotely and involve data, AWS Machine Learning roles are more cloud and deployment-oriented, whereas Data Scientists focus on data analysis and research.

What are some common challenges faced by remote AWS Machine Learning engineers, and how can they be addressed?

Remote AWS Machine Learning engineers often face challenges related to communication and collaboration, especially when working across different time zones and with cross-functional teams. Ensuring secure access to data and cloud resources is another key concern, given the sensitive nature of many machine learning projects. To overcome these challenges, engineers should leverage AWS collaboration tools, maintain clear documentation, and participate in regular virtual meetings. Additionally, setting up robust security protocols and using AWS Identity and Access Management (IAM) helps safeguard project assets while enabling effective teamwork.
What are the most commonly searched types of Aws Machine Learning jobs in Michigan? The most popular types of Aws Machine Learning jobs in Michigan are:
What are popular job titles related to Remote Aws Machine Learning jobs in Michigan? For Remote Aws Machine Learning jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Remote Aws Machine Learning jobs in Michigan look for? The top searched job categories for Remote Aws Machine Learning jobs in Michigan are:
What cities in Michigan are hiring for Remote Aws Machine Learning jobs? Cities in Michigan with the most Remote Aws Machine Learning job openings:
Senior Data Analyst

Senior Data Analyst

Canopy

Detroit, MI • On-site, Remote

$96K - $132K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 3 days ago


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Job description

Join Canopy, a Ford-backed company, at the forefront of engineering advanced threat detection and deterrence products specifically designed for vehicles. Our mission is to eliminate vehicle crime and enhance mobility through cutting-edge consumer hardware, aftermarket connectivity, and AI-driven security solutions. As part of our team, you'll be at the forefront of innovation, helping to solve one of today's most pressing challenges with cutting-edge solutions.
As a Senior Data Analyst reporting to the Team Manager of Core AI and Data, you will spearhead the design, development, and implementation of cutting-edge machine learning models and algorithms to address intricate business challenges. Your role will involve analyzing large datasets to identify meaningful patterns, trends, and relationships, using a combination of statistical methods, machine learning techniques, and data visualization tools. Additionally, you will be responsible for developing and validating approaches that ensure accuracy, robustness, and scalability for production deployment.
Responsibilities:
  • Lead the design, development, and implementation of advanced machine learning models and algorithms to solve complex business problems.
  • Collaborate with cross-functional teams, including product managers, engineers, and business stakeholders, to identify data-driven opportunities and translate them into actionable insights.
  • Analyze large datasets to extract meaningful patterns, trends, and relationships, leveraging statistical methods, machine learning techniques, and data visualization tools.
  • Develop and validate approaches, ensuring accuracy, robustness, and scalability for deployment in production environments.
  • Communicate findings and recommendations to both technical and non-technical audiences through detailed reports, presentations, and data visualizations.
  • Mentor and provide guidance to junior data scientists and analysts, fostering a culture of continuous learning and innovation.

Requirements
  • Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
  • 5+ years of experience in data science, with a strong background in statistical analysis, machine learning, and predictive modeling.
  • Proficiency in programming languages such as Python.
  • Strong expertise in SQL and experience working with large-scale databases and data processing frameworks.
  • Demonstrated ability to work with complex data sets, including data cleaning, transformation, and feature engineering.
  • Experience with data visualization tools such as Tableau, Grafana, or Matplotlib to present insights and results effectively.
  • Strong problem-solving skills, with the ability to work independently and manage multiple projects simultaneously.
  • Excellent communication skills, both written and verbal, with the ability to convey complex technical concepts to non-technical stakeholders.

Preferred Qualifications:
  • Master's or Ph.D. in Data Science, Computer Science, Statistics, or a related field.
  • Experience with deep learning techniques and frameworks such as TensorFlow, or PyTorch.
  • Familiarity with cloud computing platforms like AWS, Azure, or Google Cloud.
  • Experience where data science has driven significant business outcomes.
  • Strong understanding of A/B testing, experimental design, and causal inference techniques.
  • Experience with MLOps practices, including model deployment, monitoring, and lifecycle management in production environments.
  • Reside within the Detroit area or nearby, with the ability to work in a hybrid environment and regularly commute to our Detroit office as needed.

Benefits
  • Comprehensive medical benefits coverage, dental plans and vision coverage.
  • Health care and dependent care spending accounts.
  • Employee and Family Assistance Program (EAP).
  • Employee discount programs.
  • Retirement plan with a generous company match.
  • Generous Paid Time Off, Sick, and Holidays
  • Family Leave (Maternity, Paternity)
  • Short- and long-term disability
  • Life insurance and accidental death & dismemberment insurance

Compensation Range
Compensation may vary depending on skills and experience.
Base Salary: $96,900 - $132,300
Diversity, Equity and Inclusion: At Canopy, we're on a mission to end theft from vehicles and revolutionize vehicle security by building cutting-edge technology. We will achieve this by prioritizing individuals and staying attuned to the evolving needs of our people, users, and industry trends. We foster a workplace culture that embraces diversity and authenticity, enabling us to flourish as a team of exceptional individuals working towards a common purpose. We gain a deeper understanding of our users' experiences by continuously improving our skills and expanding our knowledge. A more diverse, equitable, and inclusive Canopy leads to greater innovation and success.
Equal Opportunity: Canopy does not discriminate on the basis of race, sex, color, religion, age, national origin, marital status, disability, veteran status, genetic information, sexual orientation, gender identity or any other reason prohibited by law in provision of employment opportunities and benefits.

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