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No Experience Entry Level Data Science Jobs in Michigan

Geologics

Data Scientist

Sterling Heights, MI · Hybrid

$52 - $62/hr

... Data Science, Math, Statistics Rate: $52 to $62 per hour (W2 contract non-benefitted, No PTO - ever ... Experience developing requirements for collection of and follow on use of data to inform the ...

Geologics

Data Scientist

Sterling Heights, MI · Hybrid

$52 - $62/hr

... Data Science, Math, Statistics Rate: $52 to $62 per hour (W2 contract non-benefitted, No PTO - ever ... Experience developing requirements for collection of and follow on use of data to inform the ...

Woven

Senior Data Scientist - AD/ADAS

Ann Arbor, MI · On-site

$85 - $120/hr

Industry experience using Python for data science (e.g. numpy, scipy, scikit, pandas, etc.) and SQL or other languages for relational databases * Experience with a cloud platform such as (AWS, GCP ...

Domino's Pizza

Data Scientist

Ann Arbor, MI · On-site

Qualifications Years Of Experience 1 to 3 years of professional experience in data science or ... No-cost mental health support for employee and dependents Childcare tuition discounts No-cost ...

Domino's

Data Scientist

Ann Arbor, MI · On-site

Qualifications Years Of Experience 1 to 3 years of professional experience in data science or ... • No-cost fitness, nutrition, and wellness programs • Fertility benefits • Adoption ...

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All JobsData Science JobsNo Experience Entry Level Data Science JobsNo Experience Entry Level Data Science Jobs in Michigan

No Experience Entry Level Data Science information

What are common challenges faced by individuals starting in entry-level data science roles with no prior experience?

Individuals beginning in entry-level data science positions without prior experience often face challenges such as getting up to speed with real-world datasets, learning to use industry-standard tools (like Python, SQL, or Tableau), and understanding how to translate business problems into data-driven solutions. Adapting to collaborative work environments, where projects often require teamwork with analysts, engineers, and business stakeholders, can also be a learning curve. However, most organizations provide mentorship and training opportunities to help new hires develop these skills quickly and grow within the team.

What are the key skills and qualifications needed to thrive as a no experience entry level data scientist?

To thrive as a No Experience Entry Level Data Scientist, you need a solid understanding of statistics, basic programming (often Python or R), and foundational knowledge in data analysis, typically supported by a relevant degree or coursework. Familiarity with tools like Excel, Jupyter Notebook, and introductory machine learning libraries such as scikit-learn or pandas is commonly expected. Curiosity, problem-solving skills, and a willingness to learn quickly help candidates stand out in this fast-evolving field. These abilities are crucial for analyzing data effectively, drawing meaningful insights, and adapting to new technologies and challenges in data science roles.

What is a no experience entry level data science job?

No Experience Entry Level Data Science jobs are positions designed for individuals who are new to the field of data science and may not have any prior professional experience. These roles typically focus on candidates with foundational knowledge of data analysis, statistics, and basic programming skills, often gained through coursework, bootcamps, or self-study. Employers for these positions generally provide training and mentorship, allowing new hires to learn practical data science skills on the job. Such positions are a great way for beginners to gain hands-on experience and start building a career in data science.
What are popular job titles related to No Experience Entry Level Data Science jobs in Michigan? For No Experience Entry Level Data Science jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching No Experience Entry Level Data Science jobs in Michigan look for? The top searched job categories for No Experience Entry Level Data Science jobs in Michigan are:
What cities in Michigan are hiring for No Experience Entry Level Data Science jobs? Cities in Michigan with the most No Experience Entry Level Data Science job openings:
No Experience Entry Level Data Science jobs near you
Infographic showing various No Experience Entry Level Data Science job openings in Michigan as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 19% Part Time, and 4% Contract. Highlights an 93% Physical, 1% Hybrid, and 6% Remote job distribution.

Data Scientist - Machine Learning Practitioner

BlueConduit

Ann Arbor, MI • On-site

$140K - $150K/yr

Full-time

Medical, Dental, Vision, Retirement

Re-posted 23 days ago

Job description

Company overview
BlueConduit is an infrastructure analytics SaaS company and social enterprise helping communities make better, faster, and more equitable decisions about critical water infrastructure. Our founding team pioneered predictive modeling for lead service line replacement in Flint, Michigan, and BlueConduit now works with hundreds of cities and utilities across North America.
Our platform helps utilities, municipalities, government agencies, and consultants combine fragmented infrastructure records, field observations, geospatial data, and predictive models to identify risk, prioritize work, meet compliance requirements, and communicate clearly with the public. We are a remote-first team committed to using data science for social good and building tools that are trusted by the people making high-stakes infrastructure decisions.
The role
BlueConduit is hiring a Data Scientist to improve and expand the machine learning models at the core of our infrastructure analytics platform. In this role, you will work on models that help cities prioritize infrastructure investments, reduce risk, and improve drinking water outcomes. You will strengthen our existing modeling workflows, help launch new model products and asset classes, and communicate results clearly to both technical and nontechnical audiences.
This is a strong fit for someone who combines rigorous applied ML judgment with product-minded execution: you enjoy messy real-world data, care about model validation and uncertainty, can build repeatable workflows rather than one-off analyses, and like explaining technical work to people who need to act on it.
In this role you will be expected to be using the latest available AI tools to code productively. You will need to understand what you're building and coding, and understand agentic AI workflows that involve best practices, including unit tests, built-in code reviews, and extensive documentation in your commits for fellow data scientists and software engineers.
This role reports to the VP of Data Science.
What you'll do
  • Build, validate, and improve machine learning and statistical models used in BlueConduit's infrastructure analytics products
  • Help design, build, and launch new model products and model classes that broaden the assets and risks BlueConduit can predict
  • Improve data science workflows, model evaluation, reproducibility, and handoffs into software/product systems
  • Work with heterogeneous municipal, infrastructure, geospatial, and field-observation datasets to generate actionable risk predictions
  • Design validation approaches and communicate model uncertainty, limitations, and tradeoffs clearly to internal teams and customers
  • Use modern AI coding tools such as Claude Code, Codex, or similar systems to accelerate development while applying strong independent programming judgment
  • Use multiple AI agents to contribute to extremely robust workflows and code pipelines with built-in testing and reviews
  • Support customer-facing analysis and present findings in ways that are clear, accurate, and useful for nontechnical decision-makers
  • Contribute to R&D that scales the impact, reliability, and reach of BlueConduit's predictive methods

BlueConduit is a small, remote, and growing team, so this is an opportunity to shape both the role and the next generation of our data science products.
What we're looking for
  • Strong Python-based data science experience, including pandas, NumPy, scikit-learn, and production-quality analysis workflows
  • An undergraduate degree in a quantitative field (e.g., CS, math, stats, physics)
  • Experience building, validating, and improving machine learning or statistical models on messy real-world data
  • Experience building repeatable data science workflows in a product at a SaaS company or similarly operational environment
  • Ability to communicate modeling results, uncertainty, and tradeoffs clearly to technical and nontechnical stakeholders
  • Fluency using modern AI coding tools - including coordinating work of AI agents - to accelerate development, grounded in strong independent programming ability and judgment
  • Strong data visualization, verbal communication, and written communication skills
  • Comfort with Git-based development workflows
  • Attention to detail, curiosity, and commitment to building models that are understandable, usable, and trusted by the people making infrastructure decisions
  • Passion for socially impactful data science, environmental justice, and public-interest technology
We're especially interested in candidates with one or more of the following
  • A rigorous graduate degree in a quantitative field, or equivalent applied experience
  • Experience modeling asset classes beyond BlueConduit's current water distribution portfolio, such as fire risk, wastewater, hydraulic systems, climate risk, insurance risk, or other infrastructure domains
  • Experience with geospatial data, GIS systems, GeoPandas, or spatial modeling
  • Experience creating a new model product or extending an existing model product to a new domain or asset class
  • Experience with both global/cross-location models and local/site-specific models
  • Experience with methodologies beyond classical ML, such as neural networks, transformers, transfer learning, or other modern ML approaches
  • Experience with cloud-based model workflows, model tracking, versioning, Databricks, PySpark, or distributed computing
  • Familiarity with infrastructure, water quality, government data, or regulated public-sector decision environments
  • Experience working in Agile product development environments
  • Aptitude and interest in building with rapid iteration cycles involving prototyping, receiving feedback, and rebuilding
Location
Remote
Compensation
  • Expected salary range: $140,000-$150,000, commensurate with experience
  • Equity options
  • Health, vision and dental benefits
  • Simple IRA benefit with company contribution matching

Every qualified applicant will receive consideration for employment without regard to race, age, color, religion, sex, sexual orientation, or national origin.

Apply