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Hourly Python Data Science Jobs in Davison, MI (NOW HIRING)

Stellantis

Data & AI SCIENTIST

Auburn Hills, MI · On-site

Be a specialist on specific data science fields (e.g. NLP, Computer Vision, Time Series) Basic ... Strong programming skills in Python and SQL * Knowledge of advanced statistical techniques and ...

Stellantis

Data Scientist

Auburn Hills, MI · On-site

Minimum of 5 years of experience in data science, econometrics or a related field * Proficiency in Python and SQL * Hands-on experience with big data and cloud platforms such as Databricks, Snowflake ...

Stellantis

Data & AI SCIENTIST

Auburn Hills, MI · On-site

Required : • Master in Data Science / Computer Science • 5 years of relevant experience (i.e ... Spark, Databricks, Snowflake • Strong programming skills in Python and SQL • Knowledge of ...

Stellantis

Data Engineer - Supply Chain

Auburn Hills, MI · On-site

$108K - $130K/yr

... Science, Information Systems, or a related field required * 8+ years of professional experience in data engineering, analytics engineering, or data platform development * Strong proficiency in Python ...

Stellantis

Data Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

You will work at the intersection of software engineering and data science, ensuring that our data ... Comprehensive experience with one or more programming languages such as Python, Java, or Rust

Stellantis

Sr Staff Data Scientist

Auburn Hills, MI · On-site

Data science, Statistics, CS, Physics, Engineering, etc.) * 8+ years of total experience in data ... Expert-level proficiency in Python (or R) and SQL for feature engineering and modeling. * Deep ...

Stellantis

Data Engineer - Supply Chain

Auburn Hills, MI · On-site

$108K - $130K/yr

Required : • Bachelor's in Computer Science, Information Systems, or a related field required • ... Python and SQL for data transformation and pipeline development • Experience designing and ...

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How much do hourly python data science jobs pay per hour?

As of Jun 17, 2026, the average hourly pay for hourly python data science in Davison, MI is $53.10, according to ZipRecruiter salary data. Most workers in this role earn between $43.75 and $60.34 per hour, depending on experience, location, and employer.

What is the difference between Hourly Python Data Science vs Data Analyst?

AspectHourly Python Data ScienceData Analyst
Required SkillsPython, statistical analysis, machine learningExcel, SQL, data visualization
Work EnvironmentTech companies, startups, research labsBusiness, marketing, finance sectors
Common CertificationsPython certifications, data science coursesExcel, Tableau, SQL certifications

Hourly Python Data Science roles focus on advanced analytics, machine learning, and programming with Python, often in tech-driven environments. Data Analysts typically handle data cleaning, visualization, and reporting using tools like Excel and SQL. While both roles require data handling skills, Python Data Science positions demand programming expertise and statistical knowledge, making them more technical and specialized.

What are Hourly Python Data Science jobs?

Hourly Python Data Science jobs are roles where professionals use Python programming to analyze, interpret, and visualize data, and are paid based on the number of hours they work. These positions often involve tasks such as data cleaning, statistical analysis, machine learning, and data visualization. Hourly data science jobs offer flexibility for both employers and workers, making them popular for freelance, contract, or part-time arrangements. Python's robust libraries and tools make it a preferred language for these roles.

What are some common challenges faced by hourly Python Data Science professionals, and how can they be addressed?

Hourly Python Data Science professionals often encounter challenges such as managing multiple clients with varying expectations, adapting quickly to different data environments, and handling inconsistent workloads. To address these, it's important to establish clear communication with clients about project scope and deadlines, maintain well-organized code and documentation for easy context switching, and utilize tools like version control and virtual environments. Building a strong personal workflow and prioritizing time management can help ensure high-quality deliverables across diverse projects.

What are the key skills and qualifications needed to thrive as an Hourly Python Data Science professional, and why are they important?

To thrive as an Hourly Python Data Science professional, you need a solid understanding of statistics, data analysis, and programming in Python, often supported by a degree in a quantitative field or equivalent experience. Familiarity with tools like Pandas, NumPy, scikit-learn, and data visualization libraries, as well as experience with version control systems like Git, is typically required. Strong problem-solving abilities, effective communication, and adaptability help you deliver insights and solutions to clients efficiently. These skills ensure accurate analysis, clear reporting, and the ability to meet diverse project needs in a flexible, project-based environment.
What are popular job titles related to Hourly Python Data Science jobs in Davison, MI? For Hourly Python Data Science jobs in Davison, MI, the most frequently searched job titles are:
What cities near Davison, MI are hiring for Hourly Python Data Science jobs? Cities near Davison, MI with the most Hourly Python Data Science job openings:
Hourly Python Data Science jobs near you
Data & AI SCIENTIST

Data & AI SCIENTIST

Stellantis

Auburn Hills, MI • On-site

Full-time

Posted yesterday

Stellantis rating

7.4

Company rating: 7.4 out of 10

Based on 124 frontline employees who took The Breakroom Quiz

17th of 44 rated automakers

Job description

The candidate will be responsible for developing advanced data use cases in Stellantis Global Supply Chain business domain, leveraging 360° ecosystem (Supply Chain, Manufacturing, Engineering, Sales and Marketing, and Purchasing. The candidate will work in a very diverse, international and challenging environment, in close collaboration with business stakeholders and data engineering teams. The candidate will have strong experience in building and implementing models, using/creating algorithms and creating/running simulations. As well as using a variety of data mining/data analysis methods.
Job responsibilities include but not limited to:
  • Merge large, complex data sets that meet business requirements
  • Analyze large amounts of information to discover trends and patterns
  • Build predictive models and machine-learning algorithms
  • Writing and refactoring the code into reusable libraries and API
  • Support business analytics initiatives across SC departments
  • Facilitate the internal and external data science & AI network
  • Be a specialist on specific data science fields (e.g. NLP, Computer Vision, Time Series)

Basic Qualifications:
  • Master in Data Science / Computer Science
  • 5 years of relevant experience (i.e. ICT and/or Supply Chain)
  • Knowledge of at least one of some of the main Big Data frameworks and platforms: Spark, Databricks, Snowflake
  • Strong programming skills in Python and SQL
  • Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests, ...)
  • Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, ...) and their real-world advantages/drawbacks
  • Combination of business focus, analytical and problem-solving skills to quickly define a data-driven solution within different initiatives
  • Ability to work within a team and with a proactive attitude

Preferred Qualifications:
  • PhD
  • Experience in a multinational (global) work environment
  • AI: mastery in one AI field such as Natural Language Processing or Computer Vision is appreciated
  • Palantir Foundry platform
  • Microsoft PowerBI / Fabrics tool (incl. DAX programming language)
  • Deep learning frameworks (Pytorch, Tensorflow, ...)
  • Ability to communicate and summarize technical topics for non-technical audience (incl. leadership)

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