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Remote Data Scientist Deep Learning Jobs in Michigan

Data Scientist

Dearborn, MI ยท On-site +1

$128K - $186K/yr

Will your career be a deep dive into what you love, or a series of new teams and new skills? Will ... learning services. 3. A/B testing design, implementation, and analysis, and experimental design ...

Will your career be a deep dive into what you love, or a series of new teams and new skills? Will ... Benefit Summary This role is remote but if you live within 50 miles within Dearborn, MI, you will ...

Data Scientist

Dearborn, MI ยท On-site +1

$107K - $182K/yr

Apply the most relevant quantitative modeling techniques and tools in statistical analysis, econometrics, operation research/optimization, data science, machine/deep learning techniques to a variety ...

Drive the future of AIpowered decisionmaking by leading sophisticated machine learning and GenAI ... Join our dynamic, centralized Data Science team as we execute our AI/ML roadmap! We focus on ...

Machine Learning Tutor

Ann Arbor, MI ยท Remote

$18 - $40/hr

... deep learning fundamentals. Ability to explain linear regression, decision trees, random forests, support vector machines, and neural network architectures while preparing students for data science ...

Machine Learning Tutor

Kalamazoo, MI ยท Remote

$18 - $40/hr

... deep learning fundamentals. Ability to explain linear regression, decision trees, random forests, support vector machines, and neural network architectures while preparing students for data science ...

Machine Learning Tutor

Detroit, MI ยท Remote

$18 - $40/hr

... deep learning fundamentals. Ability to explain linear regression, decision trees, random forests, support vector machines, and neural network architectures while preparing students for data science ...

Senior Data Analyst

Detroit, MI ยท On-site +1

$96K - $132K/yr

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 ...

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Remote Data Scientist Deep Learning information

What are the key skills and qualifications needed to thrive as a Remote Data Scientist specializing in Deep Learning, and why are they important?

To thrive as a Remote Data Scientist specializing in Deep Learning, you need a strong background in mathematics, statistics, programming (especially Python), and experience with deep learning frameworks such as TensorFlow or PyTorch, often supported by a relevant degree. Familiarity with cloud platforms (e.g., AWS, GCP), version control systems like Git, and certifications in machine learning are highly beneficial. Strong analytical thinking, problem-solving abilities, and effective remote communication skills help you stand out in this position. These skills and qualities are essential for designing robust models, collaborating with distributed teams, and delivering impactful AI solutions.

How do Remote Data Scientists specializing in Deep Learning typically collaborate with cross-functional teams?

Remote Data Scientists in Deep Learning often work closely with software engineers, product managers, and domain experts through virtual meetings, shared documentation, and version-controlled code repositories. They collaborate on defining project goals, sharing model insights, and integrating machine learning solutions into products. Effective communication and clear documentation are crucial, as team members may be in different time zones or have varying technical backgrounds. Tools like Slack, JIRA, and GitHub are commonly used to streamline collaboration and track progress.

What are remote data scientists specializing in deep learning?

Remote data scientists specializing in deep learning are professionals who use advanced machine learning techniques, particularly deep neural networks, to analyze large amounts of data and extract meaningful insights. They work from remote locations, leveraging digital tools to build, train, and deploy deep learning models for tasks such as image recognition, natural language processing, and predictive analytics. These experts collaborate with other team members virtually, contributing to projects in industries like healthcare, finance, and technology without needing to be physically present in an office.
What are the most commonly searched types of Data Scientist Deep Learning jobs in Michigan? The most popular types of Data Scientist Deep Learning jobs in Michigan are:
What are popular job titles related to Remote Data Scientist Deep Learning jobs in Michigan? For Remote Data Scientist Deep Learning jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Remote Data Scientist Deep Learning jobs in Michigan look for? The top searched job categories for Remote Data Scientist Deep Learning jobs in Michigan are:
What cities in Michigan are hiring for Remote Data Scientist Deep Learning jobs? Cities in Michigan with the most Remote Data Scientist Deep Learning job openings:
Data Scientist - Machine Learning Practitioner

Data Scientist - Machine Learning Practitioner

BlueConduit

Ann Arbor, MI โ€ข On-site, Remote

$140K - $150K/yr

Full-time

Medical, Dental, Vision, Retirement

Posted 10 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