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Hourly Python Data Science Jobs in Michigan (NOW HIRING)

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 ...

Hello Innovation

Director of Data Science

Detroit, MI · On-site

  • Medical

  • Dental

  • Vision

  • Retirement

As our Director of Data Science you will set the foundation that powers impactful data-driven ... Skilled in SQL, Python, and R, you navigate platforms like Fivetran, Snowflake, and DBT with ease.

Td

Principal Data Scientist (US)

Southfield, MI · On-site

$148K - $223K/yr

Is familiar with the business context and data infrastructure and can translate business problems to viable data science solutions * Uses a wide range of programing languages (e.g. Python) and ...

TD Bank Group

Principal Data Scientist (US)

Southfield, MI · On-site +1

$148K - $223K/yr

Is familiar with the business context and data infrastructure and can translate business problems to viable data science solutions * Uses a wide range of programing languages (e.g. Python) and ...

Munich Re

Data Scientist

Ann Arbor, MI · On-site +1

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Join our dynamic, centralized Data Science team as we execute our AI/ML roadmap! We focus on ... Proficiency in statistical programming languages such as R, Python, SAS, or similar, alongside ...

Corporate Services

Lead Data Scientist

Detroit, MI

... data science solutions. Lead Data Scientist architects, defines, and design the data science ... Python, R or SAS. Two plus (2+) years of experience involving quantitative data analyses for ...

Ford Motor Company

Data Scientist

Dearborn, MI · Remote

  • Medical

  • Dental

  • Vision

  • Life

  • PTO

... Science, Operations Research, or equivalent field. * 3+ years of experience developing analytical or optimization models in Python. * Experience building and maintaining data pipelines using SQL and ...

Socket.dev

Data Scientist

Plymouth, MI · On-site

$90 - $130/hr

... Python/R, LLM, and related technologies. * Build, maintain, and optimize ETL/ELT pipelines that ... Bachelor's degree in Data Science, Computer Science, Information Systems, Finance, Quantitative ...

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Hourly Python Data Science information

What is an hourly Python data science job?

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 the key skills and qualifications needed to thrive as an hourly Python data science professional?

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 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 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 the most commonly searched types of Python Data Science jobs in Michigan?

The most popular types of Python Data Science jobs in Michigan are:

What cities in Michigan are hiring for Hourly Python Data Science jobs?

Cities in Michigan with the most Hourly Python Data Science job openings:

Hourly Python Data Science jobs near you

Data Scientist

Stellantis

Auburn Hills, MI • On-site

Full-time

Re-posted 26 days ago

Stellantis rating

7.5

Company rating: 7.5 out of 10

Based on 131 frontline employees who took The Breakroom Quiz

14th of 44 rated automakers

Job description

The Commercial Analytics team is looking for a Data Scientist to join our team. Your mission is to build and scale trusted data science products that power marketing performance measurement while promoting data science best practices, actionable recommendations and a high bar for model quality and reliability.
Data scientists work closely with data engineers, analysts, and business teams to design analytics solutions, implement advanced algorithms and evaluate the performance of use cases. Ideal candidates are self-motivated, inquisitive and creative, with a strong desire to solve real-world problems using data.
In this role, you will:
  • Collaborate with business stakeholders to identify high-impact opportunities for statistical and machine learning use cases
  • Design and implement econometric and causal inference models to quantify the impact of vehicle incentives, pricing, and commercial levers on sales, margin, and demand
  • Estimate and interpret price and incentive elasticities across brands, segments, and regions, informing pricing and go-to-market strategies
  • Develop defensible, well-documented methodologies that stand up to executive scrutiny and support strategic decision-making
  • Communicate complex results clearly to both technical and non-technical audiences
  • Partner with Data Engineers to define and source relevant data features for modeling as well as drive adoption and a deep understanding of proper data usage
  • Develop and validate predictive models using techniques such as regression, random forests, gradient boosting, causal modeling and neural networks
  • Communicate findings and recommendations to non-technical audiences through clear visualizations and storytelling
  • Contribute to the maintenance of models in production environments, ensuring scalability and performance
  • Conduct peer code reviews and support best practices in model development and deployment
  • Collaborate with both external and internal resources to support business requirements and key KPI measurement

Basic Qualifications:
  • Bachelor's degree in a quantitative discipline (e.g., Statistics, Economics or other quantitative field)
  • 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 or Spark
  • Exposure to MLOps best practices, including model versioning, monitoring, and deployment pipelines
  • Strong grasp of machine learning algorithms like:
    • Regression (linear, logistic)
    • Causal Inference Models (Difference-in Difference, Regression Discontinuity Design)
  • Experience with experimental design, and statistical inference
  • Ability to translate complex data into actionable insights for business stakeholders

Preferred Qualifications:
  • Master's degree in a quantitative discipline (e.g., Statistics, Economics or other quantitative field)
  • Automotive experience
  • Tree-based models (Random Forest, XGBoost, LightGBM)
  • Clustering and dimensionality reduction (e.g., LDA, PCA, Dynamic Time Warping)
  • Experience using PySpark for distributed data processing and feature engineering
  • Experience with Power BI or similar tools for data visualization and dashboarding
  • 2+ years of experience working with finance / pricing / incentives data
  • 2+ years of experience working with sales / commercial data
  • Strong communication and storytelling skills with the ability to influence decision-makers
  • Understanding of CI/CD workflows for automating model testing and deployment
  • Experience working with real-time data pipelines and event-driven architectures

What Stellantis employees say

Pay

Benefits

Hours and flexibility

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