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Contract Machine Learning Data Scientist Jobs in Michigan

Saanvi Technologies

Machine Learning Engineer 3

Dearborn, MI · 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 ...

Denso

Data Scientist 2

Southfield, MI · On-site

$90K - $113K/yr

Under moderate supervision, the Data Scientist applies advanced statistical, machine learning, and artificial intelligence techniques to solve complex business problems across the enterprise. This ...

Denso

Data Scientist 2

Southfield, MI

$90K - $113K/yr

Under moderate supervision, the Data Scientist applies advanced statistical, machine learning, and artificial intelligence techniques to solve complex business problems across the enterprise. This ...

Delta Dental of Michigan

Data Scientist

Okemos, MI · Hybrid

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.

Delta Dental of Michigan

Data Scientist

Okemos, MI · On-site

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.

General Motors

AI/ML Data Scientist (GPSSC)

Warren, MI · On-site

As an AI/ML Data Scientist, you will be responsible for working with our customers to understand ... Train new machine learning models to solve complex business problems. * Prototype new AI solutions ...

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Contract Machine Learning Data Scientist information

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 are the key skills and qualifications needed to thrive as a Contract Machine Learning Data Scientist, and why are they important?

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.

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 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 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:
Contract Machine Learning Data Scientist jobs near you
Sr. Staff Data Scientist - Machine Learning & AI (Quality, Vehicle & Engineering Analytics)

Sr. Staff Data Scientist - Machine Learning & AI (Quality, Vehicle & Engineering Analytics)

Stellantis

Auburn Hills, MI • On-site

Full-time

Posted 7 hours ago

Stellantis rating

7.5

Company rating: 7.5 out of 10

Based on 128 frontline employees who took The Breakroom Quiz

15th of 44 rated automakers

Job description

About the Role:
We are looking for a Senior Staff Data Scientist (ML/AI) to serve as a technical leader, architect, and individual contributor within the Machine Learning & AI Engineering team at Stellantis.
This role sits at the intersection of machine learning, advanced analytics, experimentation, and large-scale vehicle/IoT data systems. You will define and influence how ML and AI are used across vehicle quality, engineering systems, and customer experience outcomes.
This is a high-impact, senior IC role (Staff/Principal level influence) responsible for shaping technical strategy, designing scalable ML systems, and driving measurable business outcomes such as quality improvement, warranty reduction, and customer experience enhancement.
What You Will Do:
Technical Leadership & ML Strategy (Staff-Level Ownership)
  • Define and evolve the ML/AI architecture and framework supporting quality, engineering, and vehicle analytics across the organization
  • Set technical direction for:
    • Machine learning systems
    • Experimentation platforms
    • Data science architecture
  • Act as a trusted technical advisor to senior leadership on:
    • Model feasibility
    • Trade-offs (accuracy, scalability, cost, interpretability)
    • Business impact of ML/AI initiatives
  • Influence roadmap decisions across engineering and product organizations

Advanced Machine Learning & Statistical Modeling
  • Develop and deploy predictive, prescriptive, and causal models using:
    • Vehicle data
    • IoT sensor data
    • Enterprise datasets
  • Apply advanced techniques including:
    • Statistical modeling
    • Machine learning algorithms
    • Deep learning / neural networks
  • Lead root cause analysis for vehicle quality, performance, and system failures
  • Design and build LLM-based systems and agentic AI solutions for engineering and quality use cases

Data Science Platform & Scalable Systems
  • Architect and guide development of large-scale distributed data and ML systems
  • Build and scale analytics pipelines using Spark-based distributed processing frameworks
  • Lead ML model lifecycle management, including:
    • Training
    • Validation
    • Deployment
    • Monitoring in production
  • Ensure models and systems are:
    • Explainable
    • Reliable
    • Production-ready
    • Compliant with automotive/regulatory standards

Experimentation & Product Impact
  • Own and evolve the experimentation framework/platform for safe, scalable testing of vehicle and software features
  • Design statistically sound experiments (A/B tests and beyond)
  • Translate experimental results into clear product and engineering decisions
  • Drive measurable business outcomes including:
    • Warranty cost reduction
    • Improved product quality
    • Enhanced customer experience
    • Revenue-impacting insights

Influence, Mentorship & Knowledge Sharing
  • Mentor senior and mid-level data scientists, raising technical standards across the team
  • Help teams with:
    • Problem formulation
    • Research design
    • Statistical interpretation
  • Contribute to internal knowledge systems and external-facing technical content (e.g., blogs or papers)
  • Serve as a cross-functional leader bridging engineering, product, and executive teams

What Success Looks Like (Top Performers)
Strong candidates will demonstrate:
  • Proven impact from deployed ML systems or production analytics products
  • Quantifiable improvements in:
    • Vehicle quality
    • Warranty reduction
    • Customer experience metrics
  • Ability to influence technical strategy beyond their immediate team
  • Strong communication skills with executive and non-technical stakeholders

Demonstrated ability to turn complex analysis into business decisions and outcomes
Basic Qualifications:
  • Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field
  • A minimum of 8 years of experience in data science, advanced analytics, or machine learning, including a minimum of 5 years of hands-on experience with Databricks, Palantir, Snowflake, or AWS SageMaker
  • Expert-level proficiency in:
    • Python (or R)
    • SQL
  • Strong foundation in:
    • Machine learning algorithms
    • Statistical modeling
    • Neural networks / deep learning
  • Experience building ML solutions on distributed systems (e.g., Spark)

Preferred Qualifications:
  • Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field
  • Experience with:
    • Large Language Models (LLMs)
    • Fine-tuning foundation models
    • Agentic AI systems
  • Experience building ML solutions in engineering, automotive, propulsion, or battery systems
  • Strong understanding of vehicle quality (QA), reliability, or manufacturing analytics
  • Experience working in high-scale enterprise or regulated environments

What Stellantis employees say

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Benefits

Hours and flexibility

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