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Weekend Data Science Jobs in Novi, MI (NOW HIRING)

Ford Motor Company

Senior Data Scientist

Dearborn, MI · On-site

Master's degree in quantitative fields, such as Data Science, Engineering, Operations Research, Industrial Engineering, Statistics, Mathematics OR Computer Science or equivalent combination of ...

Conclusive Marketing

Data Scientist

Detroit, MI

Data Scientist Role Summary OneMagnify's Data Scientists sit at the intersection of client strategy ... BA/BS in Computer Science, Statistics, Mathematics, MIS, Marketing Research, or a related ...

Ford Motor Company

Data Scientist

Dearborn, MI · Remote

Bachelor's degree in Data Science, Engineering, Mathematics, Computer Science, Operations Research, or equivalent field. * 3+ years of experience developing analytical or optimization models in ...

Domino's Corporate

Data Scientist

Ann Arbor, MI

Qualifications Years Of Experience 1 to 3 years of professional experience in data science or related analytical roles. Education Completion of a degree in a quantitative field such as Computer ...

Domino's Pizza

Data Scientist

Ann Arbor, MI · On-site

Qualifications Years Of Experience 1 to 3 years of professional experience in data science or related analytical roles. Education Completion of a degree in a quantitative field such as Computer ...

Domino's

Data Scientist

Ann Arbor, MI · On-site

Qualifications Years Of Experience 1 to 3 years of professional experience in data science or related analytical roles. Education Completion of a degree in a quantitative field such as Computer ...

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All JobsData Science JobsWeekend Data Science JobsWeekend Data Science Jobs in Novi, MI

Weekend Data Science information

See Novi, MI salary details

$35.2K

$115.2K

$184.4K

How much do weekend data science jobs pay per year?

As of Aug 11, 2026, the average yearly pay for weekend data science in Novi, MI is $115,152.00, according to ZipRecruiter salary data. Most workers in this role earn between $92,400.00 and $127,600.00 per year, depending on experience, location, and employer.

Do weekend data scientists work on weekends?

Weekend data scientists may work on weekends if their projects or deadlines require it, but many roles follow a standard weekday schedule. Flexibility depends on the employer, project needs, and whether the position involves on-call or urgent tasks. Typically, data science roles are performed during regular business hours, but some positions may require weekend work for data collection, analysis, or reporting.

What skills and qualifications are needed to thrive as a weekend data scientist?

To thrive as a Weekend Data Scientist, you need strong analytical skills, proficiency in statistics, and expertise in programming languages such as Python or R, often supported by a degree in a quantitative field. Familiarity with data analysis tools like SQL, machine learning libraries (e.g., scikit-learn, TensorFlow), and data visualization platforms (e.g., Tableau) is typically required. Excellent time management, problem-solving ability, and effective communication are crucial soft skills for delivering insights on tight weekend deadlines. These skills ensure that data-driven decisions can be made efficiently and accurately, even within limited time frames.

What is a weekend data science?

A Weekend Data Science job typically refers to a part-time or contract-based data science position where the primary work hours are on weekends. These roles are ideal for students, professionals seeking extra income, or those looking to gain experience in the data science field without committing to a full-time weekday schedule. Weekend data scientists analyze data, build models, and generate insights just like full-time data scientists but with flexible or reduced hours that fit around a weekend schedule.

What challenges do data scientists working on weekends face, and how can they be managed?

Data scientists working weekend shifts often encounter challenges such as limited access to colleagues for collaboration or support, since many team members may not be available outside standard business hours. Additionally, urgent issues or data anomalies may require quick, independent problem-solving. Proactive communication with weekday teams, thorough documentation, and setting up clear protocols for handoffs can help manage these challenges and ensure smooth workflow continuity.

What is the difference between Weekend Data Science vs Part-Time Data Analyst?

AspectWeekend Data SciencePart-Time Data Analyst
CredentialsTypically requires a degree in data science, statistics, or related fieldOften requires a degree or relevant experience in data analysis or related fields
Work EnvironmentProject-based, flexible hours, often remote or on-site during weekendsFlexible hours, may be remote or on-site, often with less technical complexity
Industry UsageUsed in tech, finance, healthcare, and startups for specialized projectsCommon in retail, marketing, and small businesses for routine data tasks

Weekend Data Science roles focus on complex data projects requiring advanced skills, often during weekends, while Part-Time Data Analysts handle routine data tasks with less technical depth, offering flexible schedules. Both roles serve different needs but share a focus on data work outside standard hours.

What are the most commonly searched types of Data Science jobs in Novi, MI? The most popular types of Data Science jobs in Novi, MI are:
What are popular job titles related to Weekend Data Science jobs in Novi, MI? For Weekend Data Science jobs in Novi, MI, the most frequently searched job titles are:
What job categories do people searching Weekend Data Science jobs in Novi, MI look for? The top searched job categories for Weekend Data Science jobs in Novi, MI are:
Weekend Data Science jobs near you
Infographic showing various Weekend Data Science job openings in Novi, MI 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, with an average salary of $115,152 per year, or $55.4 per hour.

Senior Data Scientist - Metrics

May Mobility

Ann Arbor, MI • On-site

Full-time

Re-posted 6 days ago

Job description

Job Summary:
May Mobility is transforming cities through autonomous technology to create a safer, greener, more accessible world. The Senior Data Scientist will shape how the company evaluates autonomous vehicle performance, uncover system vulnerabilities, and ensure safety and passenger experience standards are met.
Responsibilities:
• Develop and refine safety and comfort metrics for evaluating autonomous vehicle performance across real-world and simulation data.
• Build ML and non-ML models to detect unsafe, uncomfortable, or anomalous behaviors.
• Analyze large-scale drive logs and simulation datasets to identify patterns, regressions, and system gaps.
• Collaborate with perception, prediction, behavior, and simulation teams to integrate metrics into workflows.
• Communicate insights and recommendations to engineering leaders and cross-functional teams.
Qualifications:
Required:
• B.S, M.S. or Ph.D. Degree in Engineering, Data Science, Computer Science, Math, or a related quantitative field.
• 5+ years of experience in data science, applied machine learning, robotics, or autonomous systems.
• 2+ years working in AV, ADAS, robotics, or another safety-critical domain involving vehicle behavior analysis.
• Demonstrated experience developing or evaluating safety and/or comfort metrics for autonomous or robotic systems.
• Hands-on experience working with real-world driving logs and/or simulation data.
Preferred:
• Background in motion planning, behavior prediction, or multi-agent interaction modeling.
• Experience designing metric-driven development, KPIs, and automated triaging pipelines.
Company:
May Mobility is a manufacturing firm that designs and develops autonomous technology vehicles for self-driving transportation solutions. Founded in 2017, the company is headquartered in Ann Arbor, USA, with a team of 201-500 employees. The company is currently Growth Stage.

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