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Tesla Data Science Jobs in Michigan (NOW HIRING)

Tesla Data Science information

See Michigan salary details

$32.7K

$107K

$171.3K

How much do tesla data science jobs pay per year?

As of Jul 15, 2026, the average yearly pay for tesla data science in Michigan is $106,978.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,900.00 and $118,500.00 per year, depending on experience, location, and employer.

Is 40 too late for data science?

Age is not a barrier to becoming a data scientist, including for roles like Tesla Data Science. Success depends on skills, experience, and continuous learning, such as mastering programming languages like Python or R and understanding machine learning concepts. Many professionals transition into data science later in their careers and find opportunities regardless of age.

What does a Tesla Data Scientist do?

A Tesla Data Scientist analyzes large sets of data to provide insights and support decision-making across various departments, such as engineering, manufacturing, and energy. They use advanced statistical techniques, machine learning, and data visualization to solve complex problems and improve Tesla's products and processes. Working at Tesla often means collaborating with cross-functional teams and working in a fast-paced, innovative environment. Their work can impact vehicle performance, energy efficiency, manufacturing quality, and customer experience.

How does a Data Scientist at Tesla typically collaborate with cross-functional teams to drive impactful projects?

At Tesla, Data Scientists frequently collaborate with engineers, product managers, and business analysts to turn complex data into actionable insights. This often involves participating in regular meetings, aligning on project goals, and communicating findings to both technical and non-technical stakeholders. Data Scientists work closely with software and hardware teams to design experiments, validate models, and implement data-driven solutions that improve products or operations. Effective communication and teamwork are key, as many projects are fast-paced and require input from multiple disciplines.

Is it difficult to get hired at Tesla?

Getting hired as a Data Scientist at Tesla can be competitive, as the company seeks candidates with strong technical skills, relevant experience, and a background in data analysis, machine learning, or related fields. The hiring process typically involves multiple interviews, technical assessments, and a review of project work or portfolios. Candidates who demonstrate expertise in programming languages like Python or R, along with knowledge of big data tools, tend to have better chances.

What is the difference between Tesla Data Science vs Tesla Data Engineering?

AspectTesla Data ScienceTesla Data Engineering
Required CredentialsDegree in Data Science, Statistics, or related field; experience with machine learning and analyticsDegree in Computer Science, Software Engineering, or related; experience with data pipelines and infrastructure
Work EnvironmentAnalyzing data, building models, interpreting resultsDeveloping and maintaining data infrastructure, ETL processes
Employer & Industry UsageUsed across Tesla for product insights, autonomous driving, energy solutionsSupports Tesla's data infrastructure, ensuring data availability and quality

Tesla Data Science focuses on analyzing data and building predictive models to inform decisions, while Tesla Data Engineering centers on creating and maintaining the data infrastructure that enables data collection and processing. Both roles are essential and often collaborate within Tesla's data ecosystem.

What are the key skills and qualifications needed to thrive as a Tesla Data Scientist, and why are they important?

To thrive as a Tesla Data Scientist, you typically need a strong background in statistics, machine learning, and programming (especially Python or R), supported by a relevant degree in computer science, engineering, or a related field. Experience with big data tools like SQL, Spark, and data visualization platforms, as well as familiarity with cloud computing and Tesla's proprietary systems, is often required. Exceptional problem-solving, communication, and collaboration skills distinguish top performers in this dynamic environment. These skills are crucial for analyzing large-scale data to drive innovation and support Tesla's data-driven decision-making.

Does Tesla hire data scientists?

Yes, Tesla hires data scientists to work on projects related to vehicle automation, energy products, and manufacturing processes. Data scientists at Tesla typically need strong skills in machine learning, data analysis, and programming languages like Python or R, often working in a collaborative environment with cross-disciplinary teams.

How much is a Tesla Data Scientist paid?

Tesla Data Scientists typically earn between $100,000 and $150,000 annually, depending on experience, location, and education. Compensation may also include bonuses, stock options, and benefits, with roles often requiring proficiency in machine learning, data analysis, and programming tools like Python or SQL.
What are popular job titles related to Tesla Data Science jobs in Michigan? For Tesla Data Science jobs in Michigan, the most frequently searched job titles are:
Industrial AI Forward Deployed Strategist

Industrial AI Forward Deployed Strategist

Sight Machine, Inc.

Ann Arbor, MI • On-site

$150K - $200K/yr

Full-time

Medical, Life, PTO

Re-posted 2 days ago


Job description

Team Culture
Great things happen when people can bring their authentic selves to work. We empower all of our employees to share their perspectives, passions and experiences because collectively we make a better, stronger team. Our team members collaborate closely with peers & cross functional stakeholders throughout the business, our clients on the forefront of digital transformation, and the cutting edge of digital manufacturing thought leadership.
We take pride in our self-starter culture where employees are enabled and encouraged to achieve their professional goals through leadership guidance, learning and development. Our philosophy is that careers are continuous journeys, and we dedicate time and offer resources so that employees can reach their full potential.
Benefits + Perks
We value you at and outside of work and know your loved ones are important. Our benefits are designed to support you and your family's health through life's expected and unexpected events.
Our Benefits Include:
  • Competitive Salary + Stock Options
  • Health Care Coverage + Life Insurance + Health Savings Account + Flexible Spending
  • Account (includes spouse + children)
  • Flexible Vacation Policy
  • Adaptable Working Schedule and Environment
  • Our Perks Include:
  • Casual Dress Attire
  • Hybrid work flexibility
  • Catered Lunches, Snacks and Beverages
  • Commuter Savings Program
  • Company Outings
  • Designated Volunteering Hours + Group Volunteer Events

Sight Machine is proud to be an equal opportunity employer and considers candidates regardless of age, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. Sight Machine also considers qualified applicants regardless of criminal histories, consistent with legal requirements.
About Sight Machine, Inc.
Sight Machine strengthens manufacturers by providing the industry's only standard data model and system-level visualization capabilities. By integrating all crucial data into a single innovative platform, everyone involved in the fabrication process can visualize, contextualize and examine data in one intuitive interface.
Sight Machine is committed and mission-driven to improve lives, strengthen communities and make the world cleaner through continuously re-envisioning manufacturing processes - making them more efficient, sustainable and absolute. Founded in Michigan in 2011 and expanded to San Francisco in 2012, Sight Machine blends the spirit of technology innovation and the down to earth style of Detroit manufacturing. Our team includes early leadership from Yahoo, Tesla Motors and Oracle. Together, we share wide industry knowledge and a commitment to advance manufacturing to a more sustainable future.
At Sight Machine, you will work with manufacturing leaders in the automotive, medical device, apparel, construction, and pharmaceutical industries. You will have access to, and work with massive amounts of factory floor data to help uncover insights on how customers make products and develop solutions to pressing business problems. The platform solves problems like Extract Transform Load (ETL), information retrieval, data aggregation and analytics, factory automation, distributed computing, and security.
We place great value on professional, technical, and personal growth in an inclusive, collaborative environment. The ideal candidate will have a passion for technology and a strong can-do attitude.
About the Industrial AI Forward Deployed Strategist Role
As an Industrial AI Forward Deployed Strategist, you will lead the strategic transformation of manufacturing enterprises through Sight Machine's category-defining Manufacturing Data Platform. You will be the product manager and strategic architect for complex client engagements, defining use cases, orchestrating delivery, and ensuring AI-enabled solutions drive measurable business outcomes for some of the world's most iconic manufacturers and technology providers, including industry leaders like Microsoft, Siemens, and Databricks. If you have deep manufacturing domain expertise, strategic business acumen, and the ability to translate complex operational challenges into AI-powered solutions, this position offers the opportunity to drive game-changing digital transformation at enterprise scale while working at the forefront of Industrial AI innovation.
Why Join Sight Machine's Services Team
Our team is a hungry, humble, smart group of outcomes leaders, data scientists, data architects and engineers, software developers, and customer engagement managers who collaborate to solve some of the most complex challenges facing our manufacturing customers. We are laser-focused on trusting and empowering each other, solving today's problems (while knowing tomorrow will bring a few more), and getting a little better every day.
Our Team-Based Delivery Model
At Sight Machine, we deploy customer engagements through integrated three-person teams, each bringing complementary expertise to drive transformation:
• Account Lead - Owns the strategic "why," ensuring executive alignment and focusing the team on delivering enterprise-scale business outcomes
• Industrial AI Forward Deployed Strategist (you) - Serves as product manager and strategic architect, defining the "what" should be built based on deep business context, manufacturing expertise, and AI/ML strategic application
• Forward Deployed Engineer (FDE) - Ensures the "how," coordinating technical delivery and maintaining accountability for technical execution
As the Industrial AI Forward Deployed Strategist, you serve as the connective tissue between business strategy and technical execution. You work in close partnership with the Account Lead to maintain strategic vision while providing the Forward Deployed Engineer with clear business context and priorities. The FDE depends on you to define what needs to be built and why; you depend on the FDE to validate technical feasibility and coordinate delivery. Success requires sophisticated stakeholder management, deep industry knowledge, and the ability to bridge executive strategy with operational implementation across all three roles.
What You'll Do
Strategic Leadership & Business Architecture:
  • Own deep understanding of manufacturing operations, industry dynamics, competitive landscape, and client strategic objectives
  • Define and prioritize use cases based on business value, feasibility, and strategic alignment with enterprise transformation goals
  • Lead persona development and journey mapping to ensure solutions address real operational challenges and user needs
  • Maintain long-term strategic vision for client relationships, identifying expansion opportunities and ensuring scalable solution design
  • Translate complex manufacturing challenges into AI-enabled solution strategies that deliver measurable ROI
  • Guide clients through digital transformation journeys, managing change at organizational, process, and technology levels

Executive Stakeholder Management:
  • Build trusted advisor relationships with C-suite executives, plant leadership, and operational stakeholders across complex manufacturing organizations
  • Navigate multi-layered organizational dynamics, managing competing priorities and political considerations across operations, IT/OT, data science, and business intelligence functions
  • Facilitate executive alignment on transformation priorities, success metrics, and investment decisions
  • Communicate strategic vision, progress updates, and business value realization to senior leadership with clarity and impact
  • Manage escalations and resolve business/political issues that could derail delivery

Project & Delivery Orchestration:
  • Orchestrate complex project delivery across multiple parallel workstreams, ensuring coordination, visibility, and timely execution
  • Manage project boards, tracking systems, and reporting rhythms that maintain transparency across all stakeholders
  • Lead status meetings, facilitate decision-making, and maintain project momentum through proactive issue resolution
  • Ensure nothing falls through the cracks by maintaining comprehensive oversight of dependencies and deliverables
  • Work with Forward Deployed Engineers to translate business requirements into technical specifications and validate feasibility
  • Arbitrate scope and priority decisions, making strategic trade-offs based on business value and resource constraints

Solution Design & User Experience:
  • Design user-centric AI-powered workflows and applications that address operational gaps and drive adoption
  • Iterate rapidly with end users to validate solutions match actual needs, workflows, and deliver measurable value
  • Bridge the gap between what users need and what gets built, ensuring solutions align with strategic intent and use case priorities
  • Work with the Product team to scale developed solutions and contribute to platform capability evolution
  • Maintain focus on user adoption and value realization, measuring success through business outcomes rather than technical deliverables

Industrial AI & Analytics Strategy:
  • Apply deep understanding of AI/ML capabilities to manufacturing use cases, identifying high-impact opportunities for predictive analytics, optimization, and intelligent automation
  • Collaborate with data science teams to design advanced analytics that solve real manufacturing problems
  • Communicate AI/ML concepts and value propositions to non-technical stakeholders, building confidence and driving adoption
  • Stay current on Industrial AI trends, emerging technologies, and best practices, bringing thought leadership to client engagements

This position requires up to 40% domestic and international travel to client business and factory sites to facilitate workshops, conduct stakeholder meetings, walk factory floors, and lead on-site strategic sessions. The frequency of travel will vary depending on the client.
Qualifications
  • 7-10 years of professional experience with significant time in manufacturing operations, industrial technology, or management consulting focused on manufacturing
  • Deep domain expertise in manufacturing processes, operations management, and manufacturing technology ecosystems
  • Proven ability to manage complex stakeholder relationships at executive levels within global manufacturing organizations
  • Strong strategic thinking and business analysis skills with demonstrated ability to translate operational challenges into solution strategies
  • Exceptional communication skills with ability to influence across technical and non-technical audiences
  • Experience orchestrating complex multi-workstream projects with strong organizational and prioritization capabilities
  • Understanding of AI/ML applications in industrial contexts and ability to articulate value propositions to business stakeholders
  • Track record of driving business transformation through technology enablement

Also helpful, but not required
  • Hands-on experience with data platforms, analytics tools, or Industrial IoT technologies
  • Background in data science, industrial engineering, or operations research
  • Experience with digital transformation initiatives at enterprise scale
  • Familiarity with Azure-based data platforms and cloud infrastructure
  • MBA or advanced degree in engineering, operations, or related field
  • Prior consulting experience with top-tier strategy or technology firms

The pay range for this role is:
150,000 - 200,000 USD per year (Hybrid (San Francisco, California, US))