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Data Science Startup Jobs in Michigan (NOW HIRING)

GripFusion

Signal Processing Engineer

Ann Arbor, MI · On-site

$100K - $150K/yr

Description GripFusion is a sports-technology startup building next-generation intelligent sporting ... We operate at the intersection of hardware, software, data science, and applied biomechanics ...

GripFusion

Signal Processing Engineer

Ann Arbor, MI · On-site

$100K - $150K/yr

Description GripFusion is a sports-technology startup building next-generation intelligent sporting ... We operate at the intersection of hardware, software, data science, and applied biomechanics ...

GripFusion

Signal Processing Engineer

Ann Arbor, MI · On-site

Description GripFusion is a sports-technology startup building next-generation intelligent sporting ... We operate at the intersection of hardware, software, data science, and applied biomechanics ...

Cavallo Solutions

Product Manager

Grand Rapids, MI

Data & Analytics * Collaborate with Data Science and Engineering to define metrics, scoring models ... Operate at startup speed with established resources-the best of both worlds. * Be part of an elite ...

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All JobsData Science Startup JobsData Science Startup Jobs in Michigan

Data Science Startup information

See Michigan salary details

$20.6K

$99.1K

$184.9K

How much do data science startup jobs pay per year?

As of Jun 10, 2026, the average yearly pay for data science startup in Michigan is $99,130.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,494.00 and $137,873.00 per year, depending on experience, location, and employer.

What is a Data Science Startup job?

A Data Science Startup job involves working at an early-stage company that leverages data science to build innovative products or services. Employees typically wear multiple hats, working on data analysis, machine learning models, data pipelines, and sometimes even product or business strategy. The role often requires strong programming skills (Python, SQL), statistical knowledge, and the ability to work in a fast-paced, evolving environment. Since startups have limited resources, adaptability, problem-solving skills, and a willingness to experiment are crucial. It’s a great opportunity to gain diverse experience and make a significant impact in shaping a company's data strategy.

What are the typical challenges faced when working at a data science startup?

Working at a data science startup often involves managing ambiguity, adapting to frequently changing priorities, and balancing multiple roles due to lean team structures. You may be responsible for the entire data pipeline—from data collection and cleaning to building models and presenting findings—making flexibility and resourcefulness essential. Tight project timelines, evolving business goals, and limited initial resources can also be common, so being proactive and self-motivated helps you thrive. On the positive side, these challenges offer significant opportunities to learn rapidly, take ownership of impactful projects, and shape both the company's products and your own career trajectory.

What are the key skills and qualifications needed to thrive in the Data Science Startup position, and why are they important?

To thrive in a Data Science Startup, you need strong analytical skills, proficiency in programming languages like Python or R, and a solid understanding of statistics and machine learning. Familiarity with data visualization tools, cloud platforms, and relevant certifications such as Certified Data Scientist or AWS Certified Data Analytics are highly valued. Adaptability, creative problem-solving, and effective communication are key soft skills that set standout professionals apart in this environment. These skills are vital for driving innovation, efficiently handling rapidly changing projects, and collaborating in a fast-paced, entrepreneurial setting.

What are the most commonly searched types of Data Science Startup jobs in Michigan? The most popular types of Data Science Startup jobs in Michigan are:
What are popular job titles related to Data Science Startup jobs in Michigan? For Data Science Startup jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Data Science Startup jobs in Michigan look for? The top searched job categories for Data Science Startup jobs in Michigan are:
Data Science Startup jobs near you

Associate Product Manager @ Social app startup

Cheez

Flint, MI

Full-time

Posted 18 days ago

Job description

Cheez is a new app that sends you the pictures that your friends take of you, powered by facial recognition.

See the iOS app https://apple.co/3KLnpTa

or the Android app https://cheez.cc/449QC0Q

Responsibilities:

  • Assist in defining product requirements, objectives, and key results based on user needs and market research

  • Collaborate with the Founder/CEO, Engineering & Design team (ex-Google/Apple/Facebook/Microsoft) to prioritize, plan, and execute product roadmaps and sprint plans

  • Develop user stories, acceptance criteria, and detailed product specifications to communicate feature requirements to the design and engineering teams

  • Monitor and analyze product performance metrics, identifying opportunities for improvement and optimization

  • Conduct user research, usability testing, and competitive analysis to inform product decisions and validate hypotheses

  • Collaborate with the marketing team to create go-to-market strategies, positioning, and messaging for new features and improvements

  • Foster a culture of collaboration, continuous improvement, and user-centric thinking within the team

  • Bachelor's degree in Computer Science, Engineering, Business or a related field (preferred, not required)

  • Strong product instincts & passion for social media, technology, and staying current with industry trends

  • Excellent communication, collaboration, and presentation skills

  • Strong analytical and critical thinking abilities, with a data-driven approach to decision-making

  • Ability to thrive in a fast-paced, dynamic startup environment

  • Eagerness to learn, adapt, and contribute to a supportive, inclusive team culture

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