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Associate Data Science Analyst Jobs in Michigan (NOW HIRING)

You will own data science across simulation and synthetic data, perception and planning ML ... Drive ML and analytics applications end-to-end: dataset curation, scenario coverage, modeling ...

As the Manager, Data Science, you'll lead a team of data scientists as they apply data science to ... Query, analyze, and summarize large and complex datasets to drive business strategy and decision ...

Collaborate with the engineering and product teams to develop and support our internal data platform to support ongoing analyses * Mentor and train associate data scientists About you * 3 years of ...

Collaborate with the engineering and product teams to develop and support our internal data platform to support ongoing analyses * Mentor and train associate data scientists About you * 3 years of ...

Responsibilities : • Set and own the data science strategy across simulation and synthetic data, ML evaluation (perception, prediction, planning), fleet operations analytics, and the data platform ...

Responsibilities : • Set and own the data science strategy across simulation and synthetic data, ML evaluation (perception, prediction, planning), fleet operations analytics, and the data platform ...

The Data Science Consultant role involves solving data problems end to end, utilizing machine learning and data analysis to enhance customer value and drive business growth. Responsibilities : • ...

Required : • Minimum 5-7 years of experience in data science, analytics, or predictive modeling • Experience leading all aspects of sophisticated data science initiatives with a solid foundation ...

Profit Science: Analyze complex business problems in the distribution space and use mathematical ... Data Engineering & Navigation: Proficiency in SQL with proven experience extracting and ...

Profit Science: Analyze complex business problems in the distribution space and use mathematical ... Data Engineering & Navigation: Proficiency in SQL with proven experience extracting and ...

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Associate Data Science Analyst information

What are the key skills and qualifications needed to thrive as an Associate Data Science Analyst, and why are they important?

To thrive as an Associate Data Science Analyst, you need a solid grounding in statistics, data analysis, and programming languages such as Python or R, typically supported by a degree in a quantitative field. Familiarity with data visualization tools like Tableau, SQL databases, and potentially foundational certifications in data analytics are commonly required. Strong problem-solving, critical thinking, and effective communication skills help analysts interpret data insights and convey findings to stakeholders. These competencies are crucial for transforming raw data into actionable business intelligence and supporting data-driven decision-making.

What types of projects and datasets do Associate Data Science Analysts typically work with, and how do they contribute to larger team goals?

Associate Data Science Analysts often work on projects involving data cleaning, exploratory analysis, and basic model development using real-world datasets such as sales figures, customer behavior logs, or operational metrics. Their primary responsibility is to prepare, analyze, and visualize data to uncover insights that support business decisions. They collaborate closely with more senior data scientists, business analysts, and stakeholders to ensure that their analyses align with organizational objectives. This role provides valuable exposure to the end-to-end data science workflow and lays the foundation for advancement into more specialized or senior data science positions.

What does an Associate Data Science Analyst do?

An Associate Data Science Analyst is an entry-level professional who assists in collecting, analyzing, and interpreting data to help organizations make data-driven decisions. They work closely with senior data scientists and analysts, using statistical tools and programming languages like Python or R to process data, create reports, and visualize results. Their responsibilities often include cleaning and organizing data sets, performing exploratory data analysis, and supporting the development of predictive models. This role is a great way to gain hands-on experience in data science while building foundational skills for more advanced positions.

What is the difference between Associate Data Science Analyst vs Data Analyst?

AspectAssociate Data Science AnalystData Analyst
Required CredentialsBachelor's degree in data-related field; some roles prefer certifications in data analysis or programmingBachelor's degree in statistics, mathematics, or related field; certifications like Microsoft Excel or SQL are common
Work EnvironmentCollaborates with data scientists and engineers; involved in data modeling and analysis tasksFocuses on data collection, cleaning, and reporting; often works with business teams
Employer & Industry UsageUsed in tech, finance, healthcare industries; entry-level role in data teamsWidely used across industries for business insights and reporting

The Associate Data Science Analyst and Data Analyst roles share similarities in educational background and industry usage. However, the Associate Data Science Analyst typically involves more technical tasks like data modeling and working closely with data science teams, whereas Data Analysts focus more on data reporting and business insights. Both roles serve as entry points into data careers but differ in technical depth and collaboration scope.

What cities in Michigan are hiring for Associate Data Science Analyst jobs? Cities in Michigan with the most Associate Data Science Analyst job openings:
Director, Data Science

Director, Data Science

May Mobility

Ann Arbor, MI • On-site

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 3 days ago


Job description

Job Summary

May Mobility is entering an exciting phase of growth as we expand our autonomous transit and mobility services across the country. Founded in 2017 by a team of experienced roboticists, perception, behavior, AI, and software engineers, we operate driverless transit shuttles in real communities - not as a research demonstration, but as a daily-service product that people rely on to get to work, school, and home.

The Director, Data Science will lead the team responsible for turning the data generated by our fleet, simulation environment, and ML systems into the insights, evaluations, and decisions that make our autonomous service safer, more efficient, and ready to scale into new cities. You will own data science across simulation and synthetic data, perception and planning ML evaluation, fleet operations analytics, and the data infrastructure that supports them. You will partner directly with Engineering, Product, Operations, and Safety leadership to set measurement standards, define release criteria, and translate frontline operating data into the next generation of our autonomy stack.

This is a leadership role for someone who has scaled a data science function inside a hard-tech environment, who is comfortable making engineering and product tradeoffs alongside their team, and who sees the gap between research-grade ML and production transit-grade ML as the most interesting problem in the industry today.

Essential Responsibilities
  • Set and own the data science strategy across simulation and synthetic data, ML evaluation (perception, prediction, planning), fleet operations analytics, and the data platform that supports them; translate that strategy into a 12-24 month roadmap with measurable milestones.
  • Lead, grow, and develop a team of senior data scientists, ML engineers, and front-line managers; recruit from a small expert pool, calibrate the bar, and build a hiring brand that allows May Mobility to win against AV, robotics, and AI competitors.
  • Partner with Engineering, Product, Safety, and Operations leaders to define release criteria, performance metrics, and ODD-expansion gates; use data to make the business case for what we deploy, where, and when.
  • Drive ML and analytics applications end-to-end: dataset curation, scenario coverage, modeling, offboard evaluation, productionization, and continuous monitoring of fleet performance in the wild.
  • Establish measurement and experimentation standards across the company - including before/after analyses for stack changes, A/B-style comparisons in simulation, and statistically credible reporting on real-world incidents.
  • Lead team-wide quality activities including design and code reviews; hold the bar on engineering rigor for production data science systems.
  • Track and trend technical performance of the autonomy stack in the field; surface root causes, prioritize fixes with engineering, and represent fleet-data findings to executives, regulators, and partners.
  • Provide technical guidance to Engineering and Operations leaders on issue diagnosis, resolution, and the ML changes most likely to move our key safety and service metrics.
  • Represent May Mobility's data science work externally where appropriate - through publications, conference talks, partner reviews, and recruiting.
Skills and Abilities

Success in this role typically requires the following competencies:

  • Autonomy Data Expertise. Can reason fluently about the data produced by a modern AV stack - sensor logs, perception outputs, planning traces, simulator results, and operational telemetry - and can identify which signals matter for which decisions.
  • Hands-On Technical Depth. Has personally shipped production ML or analytics systems within the last 3-5 years and is credible in code review and design review with senior engineers and scientists.
  • Cross-Functional Translator. Can explain a complex ML or statistical finding to engineering, product, and executive audiences; and can extract a clear analytical brief from a vague business or safety question.
  • Data-Driven Decision Making. Uses fleet, simulation, and operational data to change roadmap decisions; comfortable defending a position with data and equally comfortable being wrong in front of the team when new data arrives.
  • Stakeholder Alignment. Builds durable working relationships with engineering, product, safety, and operations leaders; can broker disagreement between technical functions without escalation becoming the norm.
  • Talent Magnet and Coach. Has personally hired and developed senior data scientists and front-line managers; calibrates the bar, gives direct feedback, and grows people into bigger jobs.
  • Prioritization Rigor. Comfortable killing work that doesn't earn its place on the roadmap; protects the team from low-leverage requests while staying responsive to legitimate cross-functional needs.
Qualifications and Experience

Candidates most successful in this role typically hold the following qualifications or comparable knowledge or experience:

  • 8+ years of industry experience in data science, machine learning, or applied research, with at least 4 years managing senior individual contributors and front-line managers.
  • Direct experience leading data science or ML work in at least one of the following domains: autonomous vehicles or ADAS, robotics, large-scale computer vision systems, simulation and synthetic data, reinforcement learning, or large-scale ML platforms.
  • Demonstrated track record leading a team of 10 or more through a major delivery - for example, a production launch, a major model rollout, a regulatory milestone, or a significant ODD or product expansion.
  • Bachelor's degree in Computer Science, Statistics, Mathematics, Engineering, Physics, Robotics, or a related quantitative field, or equivalent practical experience.
  • Strong programming skills in Python; working familiarity with the production ML stack used in modern AV/robotics environments (e.g., PyTorch or TensorFlow, distributed training, dataset and feature pipelines, experiment tracking).
  • Experience setting measurement and experimentation standards inside an engineering or product organization, with credible examples of metrics or evaluation frameworks the team adopted and kept using.
  • Experience operating in cross-functional partnership with engineering, product, safety, and operations leaders - comfortable both defending technical positions and adjusting them in light of business or safety constraints.
Preferred
  • Master's or PhD in Computer Science, Robotics, Statistics, EE, Mathematics, or a related quantitative field.
  • Prior experience at an autonomous vehicle, robotics, or hard-tech company that has deployed products to real customers (not only research demos).
  • Experience with simulation, synthetic data generation, sim-to-real transfer, or scenario-based evaluation for AV or robotics.
  • Familiarity with safety-case construction, ODD definition, or regulator engagement for autonomous systems.
  • Publications or conference contributions in top-tier ML, CV, or robotics venues (e.g., NeurIPS, ICML, CVPR, ICRA, RSS).
  • Experience with C/C++ systems and/or GPU programming sufficient to engage credibly with onboard ML and infrastructure teams.
  • Demonstrated ability to mentor and grow junior managers and senior individual contributors into bigger roles.
Physical Requirements
  • Standard office working conditions which include but are not limited to prolonged sitting, standing and computer use
  • Travel Required? Moderate: 11%-25% (site visits to deployment cities, partner meetings, recruiting events, and engineering offsites).

Benefits and Perks

  • Comprehensive healthcare suite including medical, dental, vision, life, and disability plans. Domestic partners who have been residing together at least one year are also eligible to participate. 
  • Health Savings and Flexible Spending Healthcare and Dependent Care Accounts available.
  • Rich retirement benefits, including an immediately vested employer safe harbor match.
  • Generous paid parental leave as well as a phased return to work. 
  • Flexible vacation policy in addition to paid company holidays.
  • Total Wellness Program providing numerous resources for overall wellbeing   
Don't meet every single requirement? Studies have shown that women and/or people of color are less likely to apply to a job unless they meet every qualification. At May Mobility, we're committed to building a diverse, inclusive, and authentic workforce, so if you're excited about this role but your previous experience doesn't align perfectly with every qualification, we encourage you to apply anyway! You may be the perfect candidate for this or another role at May.

Want to learn more about our culture & benefits? Check out our website!

May Mobility is an equal opportunity employer.  All applicants for employment will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, gender identity or expression, veteran status, genetics or any other legally protected basis.   Below, you have the opportunity to share your preferred gender pronouns, gender, ethnicity, and veteran status with May Mobility to help us identify areas of improvement in our hiring and recruitment processes. Completion of these questions is entirely voluntary.  Any information you choose to provide will be kept confidential, and will not impact the hiring decision in any way. If you believe that you will need any type of accommodation, please let us know.

Note to Recruitment Agencies: May Mobility does not accept unsolicited agency resumes. Furthermore, May Mobility does not pay placement fees for candidates submitted by any agency other than its approved partners.