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Contract Machine Learning Data Scientist Jobs in Michigan

You will partner with data scientists, analytics leaders, IT, and manufacturing teams to move ... machine learning pipelines, including data ingestion, preprocessing, training, validation ...

Machine Learning Engineer 3

Dearborn, MI ยท On-site

$105K - $126K/yr

Machine Learning Engineering Engineer 3 Dearborn, MI W2 Position Description: We are seeking an ... This role combines expertise in Data Science, Software Engineering, and MLOps to deliver scalable ...

Data Scientist Number of Positions: 1 Location: Okemos, MI Location Specifics: Hybrid Position Job ... Applies machine learning algorithms and predictive models to solve complex business challenges.

Data Scientist Number of Positions: 1 Location: Okemos, MI Location Specifics: Hybrid Position Job ... Applies machine learning algorithms and predictive models to solve complex business challenges.

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Contract Machine Learning Data Scientist information

What is a contract machine learning data scientist?

A Contract Machine Learning Data Scientist is a professional who works on a temporary or project-based basis to build, implement, and optimize machine learning models for organizations. Unlike full-time employees, contract data scientists are hired for specific projects or timeframes and may work independently or as part of a team. Their responsibilities typically include data cleaning, feature engineering, model selection, and communicating insights to stakeholders. Contract roles offer flexibility for both the professional and the employer, often focusing on specialized tasks or filling short-term skill gaps.

What are the key skills and qualifications needed to thrive as a contract machine learning data scientist?

To excel as a Contract Machine Learning Data Scientist, you need a strong background in statistics, programming (Python/R), and applied machine learning, typically supported by a relevant degree in computer science, mathematics, or a related field. Familiarity with tools and frameworks such as TensorFlow, PyTorch, scikit-learn, cloud platforms (AWS, GCP, Azure), and version control systems is essential, along with experience deploying models in production. Exceptional problem-solving abilities, communication skills, and adaptability help you translate business needs into actionable data solutions and quickly integrate into new teams. These skills are crucial for delivering high-impact, reliable machine learning solutions on tight project timelines and in diverse organizational environments.

How do contract machine learning data scientists typically collaborate with in-house teams during a project?

Contract machine learning data scientists often work closely with in-house data teams, product managers, and engineers to align project goals and deliverables. They frequently participate in virtual meetings, code reviews, and regular progress updates to ensure transparency and seamless integration of their work. Effective communication and documentation are critical, as contractors may need to quickly adapt to the company's workflows and tools. This collaborative environment enables contractors to contribute specialized expertise while staying attuned to the broader objectives of the organization.

What is the difference between Contract Machine Learning Data Scientist vs Contract Data Scientist?

AspectContract Machine Learning Data ScientistContract Data Scientist
CredentialsTypically requires advanced degrees in data science, machine learning, or related fieldsRequires similar degrees but may have a broader focus on data analysis
Work EnvironmentOften in tech, finance, or healthcare industries focusing on ML projectsVaries across industries, including marketing, finance, and consulting
Employer UsageUsed by companies developing AI/ML solutions or productsEmployed for data analysis, reporting, and strategic insights
Search & Comparison IntentOften searched by those interested in AI/ML-specific rolesMore general, related to data analysis roles

The main difference is that Contract Machine Learning Data Scientists focus on developing and implementing machine learning models, while Contract Data Scientists may handle broader data analysis tasks without necessarily specializing in ML. Both roles require strong analytical skills and relevant credentials, but their project focus and industry applications differ.

What are popular job titles related to Contract Machine Learning Data Scientist jobs in Michigan?

For Contract Machine Learning Data Scientist jobs in Michigan, the most frequently searched job titles are:

What job categories do people searching Contract Machine Learning Data Scientist jobs in Michigan look for?

The top searched job categories for Contract Machine Learning Data Scientist jobs in Michigan are:

What cities in Michigan are hiring for Contract Machine Learning Data Scientist jobs?

Cities in Michigan with the most Contract Machine Learning Data Scientist job openings:

Data Scientist - Machine Learning Practitioner

BlueConduit

Ann Arbor, MI โ€ข On-site, Remote

$140K - $150K/yr

Full-time

Medical, Dental, Vision, Retirement

Re-posted 12 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.

Employment Type: FULL_TIME