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Quantitative Data Engineer Jobs in Michigan (NOW HIRING)

Viewline Ventures

Quantitative Team Manager

Detroit, MI · On-site

... data-driven business. Our strategies are identified by a small research team and then executed by ... Be the bridge to engineering. You will spend real time watching people work, spotting what should ...

Ford Motor Company

Data Anchor

Dearborn, MI · On-site

$85K - $192K/yr

Master's degree in Data Science, Computer Science, Computer Engineering, Statistics, or a related highly quantitative field. * Experience: 5+ years of combined experience in Data Science, Data ...

May Mobility

Director, Data Science

Ann Arbor, MI · On-site

... 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 ...

May Mobility

Director, Data Science

Ann Arbor, MI · On-site

... 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 ...

DTE Energy

Expert Data Scientist

Detroit, MI · On-site

D degree with emphasis on coursework of a quantitative nature (e.g., Statistics, Computer Science, Engineering, Mathematics, Physics, Data Science, Econometrics, etc.) * Advanced business acumen and ...

DTE Energy

Expert Data Scientist

Detroit, MI · On-site

D degree with emphasis on coursework of a quantitative nature (e.g., Statistics, Computer Science, Engineering, Mathematics, Physics, Data Science, Econometrics, etc.) * Advanced business acumen and ...

Optimal Inc.

Data Management Specialist

Dearborn, MI · Hybrid

Engineering Data Analytics Specialist - Powertrain Programs. The Engineering Data Analytics ... Automation Quantitative Analysis Data Integrity Management Business Insights Development Skills ...

New

Tech Tammina LLC

Data Analyst

Warren, MI · On-site

Bachelor's or Master's degree in Computer Science, Applied Mathematics, Statistics, Engineering, or a related quantitative field * Minimum 5 years of experience in data analytics, business ...

Consumers Energy

Data Scientist

Royal Oak, MI · On-site

Strong acumen in quantitative analytics and structured problem solving * Excellent communication ... engineering * Ability to identify the strengths and weaknesses of alternative solutions ...

CMS Energy, Corp.

Data Scientist

Royal Oak, MI · On-site

Strong acumen in quantitative analytics and structured problem solving * Excellent communication ... engineering * Ability to identify the strengths and weaknesses of alternative solutions ...

New

Consumers Energy

Data Scientist

Royal Oak, MI · On-site

Strong acumen in quantitative analytics and structured problem solving * Excellent communication ... engineering * Ability to identify the strengths and weaknesses of alternative solutions ...

Consumers Energy

Data Scientist

Royal Oak, MI · On-site

Strong acumen in quantitative analytics and structured problem solving * Excellent communication ... engineering * Ability to identify the strengths and weaknesses of alternative solutions ...

General Motors

Staff Data Scientist

Warren, MI · Hybrid

Master's in Computer Science, Engineering, Mathematics, Operations Research, Statistics, or a related quantitative field. * 10+ years of progressive experience in data science or a related analytical ...

General Motors

Staff Data Scientist

Warren, MI · On-site

Master's in Computer Science, Engineering, Mathematics, Operations Research, Statistics, or a related quantitative field. * 10+ years of progressive experience in data science or a related analytical ...

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Quantitative Data Engineer information

What is a quantitative data engineer?

A Quantitative Data Engineer is a professional who designs, builds, and maintains data infrastructure that supports quantitative analysis, typically in finance or technology sectors. They work closely with quantitative analysts and data scientists to ensure efficient data pipelines, data quality, and high-performance systems for processing large datasets. Their responsibilities include developing ETL processes, optimizing databases, and implementing data models to support research and trading strategies. Strong programming skills, expertise in big data technologies, and knowledge of quantitative methods are essential for this role.

How does a quantitative data engineer typically collaborate with data scientists and quantitative analysts on projects?

Quantitative Data Engineers work closely with data scientists and quantitative analysts to design, build, and optimize data pipelines that support complex modeling and analytics. They are often responsible for ensuring data quality, scalability, and efficient data processing, enabling analysts to focus on developing models and extracting insights. Regular collaboration includes translating analytical requirements into technical solutions, troubleshooting data issues, and iterating on data infrastructure to support evolving project needs. This teamwork fosters an environment where technical and analytical expertise complement each other, leading to more robust and actionable results.

What are the key skills and qualifications needed to thrive as a quantitative data engineer, and why are they important?

To excel as a Quantitative Data Engineer, you need strong proficiency in programming (such as Python, R, or C++), advanced mathematical and statistical knowledge, and a relevant degree in computer science, mathematics, or a related field. Experience with big data tools (like Spark, Hadoop), cloud platforms, and data pipeline systems, as well as familiarity with financial data sets, is typically required. Analytical thinking, detail orientation, and effective problem-solving skills distinguish top performers in this role. These competencies are critical for efficiently transforming complex data into actionable insights and supporting robust quantitative models in data-driven environments.

What is the difference between Quantitative Data Engineer vs Data Scientist?

AspectQuantitative Data EngineerData Scientist
Primary FocusBuilding data pipelines, data infrastructure, and ensuring data qualityAnalyzing data, creating models, and deriving insights
Skills & ToolsSQL, Python, Spark, ETL processes, data architectureStatistics, machine learning, Python/R, data visualization
CredentialsComputer science, engineering, or related degrees; certifications in data engineeringStatistics, data science, or related degrees; certifications in data analysis or machine learning
Work EnvironmentData engineering teams, data infrastructure projectsData analysis teams, research, and modeling projects

While both roles work closely with data, Quantitative Data Engineers focus on building and maintaining data systems, whereas Data Scientists analyze data to generate insights and models. They often collaborate but have distinct skill sets and responsibilities within data-driven organizations.

What are popular job titles related to Quantitative Data Engineer jobs in Michigan?

For Quantitative Data Engineer jobs in Michigan, the most frequently searched job titles are:

What job categories do people searching Quantitative Data Engineer jobs in Michigan look for?

The top searched job categories for Quantitative Data Engineer jobs in Michigan are:

What cities in Michigan are hiring for Quantitative Data Engineer jobs?

Cities in Michigan with the most Quantitative Data Engineer job openings:

Quantitative Data Engineer jobs near you
Infographic showing various Quantitative Data Engineer job openings in Michigan as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Quantitative Team Manager

Detroit, MI • On-site

Viewline Ventures
See more jobs at Viewline Venturesexternal

Full-time

Posted 17 days ago

Key responsibilities

  • Manage the execution floor day to day, including overseeing people, training, processes, error rates, and throughput.

  • Improve output per person through training, process improvements, and daily oversight, and reduce error rates by analyzing system failures and implementing solutions.

  • Own training and onboarding processes, systematize ramp-up time, and act as the bridge to engineering by translating manual workflows into technical requirements.

Job description

About Us

We are a stealth-stage fund and tech startup operating at the intersection of alternative markets and quantitative strategy. Backed by experienced operators and growing quickly, we are building the infrastructure to scale a high-performance, data-driven business.

Our strategies are identified by a small research team and then executed by an operations floor working through structured playbooks. The edge is real, but capturing it depends entirely on execution being accurate, fast and consistent. That is where this role sits.

The Role

You run the execution floor day to day so our Head of Quant can go back to research.

Today he is doing both, which means the research half is not happening and the floor half is not being managed as well as it should be. You take the floor: the people, the training, the process, the error rates and the throughput. He takes back the work only he can do.

The team you will manage is largely early in their careers, works to detailed playbooks, and is measured on output and accuracy. Output per person currently varies by a factor of several between the best and the weakest, which tells you most of what you need to know about where the opportunity is.

You do not need to be a mathematician. You need to understand the workflow completely, care intensely about error rates, and be able to turn a clunky manual process into a written specification an engineer can build.

What You'll Do

Raise output per person. Through training, better process, clearer standards and daily oversight. The spread between your best and weakest operator is the number you are attacking.

Drive error rates down and keep them down. When someone makes a mistake, your first question is what about the system allowed it. Your second is what changes so it cannot happen again.

Own training and onboarding for the floor. Ramp time is currently measured in months. You will systematise it, document it, and eventually delegate it.

Be the bridge to engineering. You will spend real time watching people work, spotting what should not be manual, and writing prioritized requirements that get built.

Keep the hopper full. Nobody on the floor should be idle waiting on equipment, a handoff or an answer. The logistics of that are yours.

Take the escalations. Ambiguous situations, unusual cases and anything the playbook does not cover come to you first.

Requirements

  • You have managed a high-volume execution, production or fulfillment floor where accuracy mattered as much as speed
  • You think in checklists, standard operating procedures and error rates. You believe a mistake is a failure of the system first and the person second
  • You are highly literate with spreadsheets and comfortable with basic data querying. You spot patterns and anomalies that individuals working alone would not
  • You write clear technical requirements. You can describe a broken workflow precisely enough that someone can build the fix
  • You are uncompromising on standards and genuinely good with early-career people. Both, not one
  • You are rigid about hitting targets and flexible about how, and you will operationalize a new playbook rather than resisting it
  • You handle sensitive data and money-adjacent workflows with discretion
Bonus Points For
  • Operations management at a trading firm, betting operation, payments company or similar
  • Technical project or program management, or technical implementation leadership
  • Managing distributed field teams across multiple states or provinces
  • A competitive background in strategy games, poker, esports or trading
  • Experience introducing measurement to a team that has never been measured

Benefits

  • Competitive base plus performance bonuses tied to floor output and accuracy
  • Direct access to the founder and the Head of Quant, with no layers in between
  • Own a function outright in a company where this function is the profit center
  • Real growth path as the floor expands into new regions

Apply