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Intern Python Data Science Jobs in Michigan (NOW HIRING)

Saanvi Technologies

Senior Data Product Manager

Dearborn, MI · On-site

$116K - $153K/yr

Master's degree in Business, Data Science, Analytics, or a related field. * Experience with cloud platforms such as Amazon Web Services, Microsoft, or Google. * Familiarity with SQL, Python, data ...

State of Michigan

Data Quality Assurance Intern

Lansing, MI · On-site

$15.25 - $20.25/hr

Intern Responsibilities / Projects: Projects could include: • Perform accurate data entry, data ... Public Health, Public Administration, Data Science, Environmental Health, or a related field ...

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 ...

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Intern Python Data Science information

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

To excel as an Intern Python Data Science, you should have a solid grasp of Python programming, statistics, and foundational data analysis concepts, typically supported by coursework or academic projects in data science or related fields. Familiarity with tools like Jupyter Notebook, Pandas, NumPy, and basic machine learning libraries such as scikit-learn is commonly expected. Curiosity, problem-solving, and the ability to communicate findings clearly are standout soft skills in this role. These competencies enable interns to effectively support data-driven projects, contribute to team goals, and develop practical experience essential for a future data science career.

What types of projects can I expect to work on as an Intern Python Data Science?

As an Intern Python Data Science, you will typically work on projects involving data cleaning, exploratory data analysis, and the development of predictive models using Python libraries like pandas, NumPy, and scikit-learn. You may be tasked with supporting ongoing research, building data visualizations, or automating data collection processes. Collaboration with data scientists and engineers is common, offering opportunities to learn best practices in code review, version control, and teamwork. These experiences provide a solid foundation for more advanced roles in data science.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as the Pareto principle, suggests that roughly 80% of results come from 20% of the efforts or data. Data scientists often focus on the most impactful features or data subsets to optimize model performance and efficiency.

What is the salary of Python intern?

The salary of a Python intern typically ranges from $15 to $25 per hour, depending on the location, company, and level of experience. Interns often receive stipends or hourly wages and may also gain valuable skills in Python programming, data analysis, and tools like Jupyter Notebook or Pandas during their internship.

Is 30 dollars an hour good for an internship?

For an intern in Python Data Science, earning $30 an hour is above average, as many internships pay between $15 and $25 per hour. This rate reflects the specialized skills in programming, data analysis, and tools like Python and Jupyter notebooks, and may indicate a more competitive or advanced internship position.

What does an Intern Python Data Science do?

An Intern Python Data Science assists data science teams with tasks such as data cleaning, analysis, and visualization, primarily using Python programming. They may work on projects involving data collection, processing, and building simple predictive models. Interns are also expected to learn and apply various data science techniques and tools, often under the guidance of experienced data scientists. This role provides hands-on experience and exposure to real-world data challenges, helping interns develop their technical and analytical skills.

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

AspectIntern Python Data ScienceIntern Data Analyst
Required SkillsPython, data analysis, machine learning basicsExcel, SQL, data visualization
Work EnvironmentTech companies, startups, research labsBusiness, finance, marketing departments
Common TasksData cleaning, modeling, scriptingData reporting, dashboard creation

Intern Python Data Science roles focus on programming, machine learning, and advanced data analysis, often in tech-driven environments. Intern Data Analyst positions emphasize data reporting, visualization, and basic analysis in business settings. While both roles require analytical skills, Intern Python Data Science roles demand coding proficiency, whereas Intern Data Analyst roles focus more on data presentation and interpretation.

Is 30 too late for data science?

Age is not a barrier to becoming a data science intern; many professionals transition into data science later in their careers. Success depends on acquiring relevant skills such as programming in Python, understanding statistics, and working with tools like Jupyter or SQL, regardless of age.
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 are popular job titles related to Intern Python Data Science jobs in Michigan? For Intern Python Data Science jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Intern Python Data Science jobs in Michigan look for? The top searched job categories for Intern Python Data Science jobs in Michigan are:
Intern Python Data Science jobs near you
Data Scientist-Direct Hire

Data Scientist-Direct Hire

US Department of the Treasury

Traverse City, MI • On-site

$74K/yr

Other

Posted 2 days ago

New

U.S. Department Of The Treasury rating

8.2

Company rating: 8.2 out of 10

Based on 13 frontline employees who took The Breakroom Quiz

227th of 673 rated public administrative organizations

Job description

WHAT IS DATA AND ANALYTICS (DAO)-RESEARCH, APPLIED ANALYTICS & STATISTICS (RAAS)?
A description of the business units can be found at: https://www.jobs.irs.gov/about/who/business-divisions

  • Position(s) are to be filled in the following area(s):
    • DAO - DATA AND ANALYTICS
  • Consider each location carefully when applying. If you are selected for a location, that location will become your official post of duty.
REVIEW THE ADDITIONAL INFORMATION BELOW FOR FURTHER DETAILSQualifications:Federal experience is not required. Experience may have been gained in the public sector, private sector or through Volunteer Service. One year of experience refers to full-time work; part-timework is considered on a prorated basis. To ensure full credit for your work experience, please indicate dates of employment by month/day/year, and indicate number of hours worked per week, on your resume.
You must meet the following requirements by the cut-off dates as shown in announcement under the 'How to Apply' section.
QUALIFICATION REQUIREMENTS: To qualify for this position, you must meet the qualification requirements outlined below:
BASIC REQUIREMENTS All GRADES: EDUCATION:
You must have a bachelor's or higher degree in mathematics, statistics, computer science, data science or other field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.
OR
COMBINATION OF EDUCATION AND EXPERIENCE: You may qualify with an equivalent combination of qualifying experience and education with at least 30 semester hours related to Mathematics, statistics, computer science, data science or field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.
EDUCATION/SPECIALIZED EXPERIENCE FOR GS-11: In addition to meeting basic requirements, to be eligible for this position, you must have at least one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-09 grade level in the Federal Service. Specialized experience for this position includes: Applying descriptive or inferential statistical methods to analyze data, identify trends or patterns, evaluate results, and develop findings, reports, or recommendations; Using programming, query, or scripting languages, such as Structured Query Language (SQL), R, Python, SAS, or equivalent tools, to extract, transform, analyze, or prepare data for analysis; Experience manipulating datasets in relational databases (e.g., Compliance Data Warehouse, Enterprise Data Platform); Applying statistical or data science techniques, such as forecasting, predictive modeling, machine learning, optimization, or exploratory data analysis, to evaluate data or support analytic findings; and Creating reports, dashboards, visualizations, written summaries, or presentations to communicate statistical or technical findings to technical or non-technical audiences.
OR
EDUCATION: You may substitute education for specialized experience as follows: A Ph.D. or equivalent doctoral degree as described in the basic requirements in mathematics, statistics, computer science, data science or field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.
OR
Three (3) full academic years of progressively higher-level graduate education leading to a PH.D or equivalent doctoral degree in mathematics, statistics, computer science, data science or field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.
OR
COMBINATION OF EDUCATION AND EXPERIENCE: You may qualify with an equivalent combination of qualifying experience and education.
SPECIALIZED EXPERIENCE GRADE 12: In addition to the basic requirements above, to be eligible for this position at the GS-12 level, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-11 grade level in the Federal service. Specialized experience for this position includes experience performing all the following:
  • Planning and carrying out data analysis assignments by applying descriptive or inferential statistical methods to analyze data from multiple sources, validate results, identify trends or patterns, and develop findings, reports, or recommendations.
  • Using programming, query, or scripting languages, such as Structured Query Language (SQL), R, Python, SAS, or equivalent tools, to extract, transform, validate, analyze, visualize, or document structured or unstructured data for data science projects.
  • Experience manipulating datasets in relational databases (e.g., Compliance Data Warehouse, Enterprise Data Platform).
  • Applying statistical or data science techniques, such as forecasting, predictive modeling, machine learning, optimization, prescriptive analysis, or exploratory data analysis, to evaluate data, models, programs, or operations and make projections or recommendations.
  • Creating and presenting reports, dashboards, visualizations, written summaries, or presentations that explain statistical or technical methods, findings, limitations, or recommendations to managers, stakeholders, customers, or project teams.

SPECIALIZED EXPERIENCE GRADE 13: In addition to the basic requirements above, to be eligible for this position at the GS-13 level, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-12 grade level in the Federal service. Specialized experience for this position includes experience performing all the following:
  • Independently planning and carrying out data science or statistical analysis projects by defining analytic questions, selecting data sources or methods, analyzing structured or unstructured data, validating results, and developing findings or recommendations.
  • Developing or applying statistical, machine learning, operations research, or other data science methods to evaluate programs, operations, compliance, or organizational performance, for example forecasting, predictive or prescriptive modeling, optimization, natural language processing or text analytics, graph or link analysis, or exploratory data analysis.
  • Using programming, query, scripting, or analytic tools, such as Structured Query Language (SQL), R, Python, SAS, or equivalent tools, to prepare, transform, document, analyze, and visualize data for data science projects.
  • Experience manipulating datasets in relational databases (e.g., Compliance Data Warehouse, Enterprise Data Platform).
  • Documenting analytic approaches, assumptions, limitations, validation results, success measures, or key performance indicators, and presenting technical findings or recommendations to managers, stakeholders, customers, or cross-functional teams.

AND
You must also meet the following requirements:
  • MINIMUM AGE REQUIREMENT: Minimum age for federal employment is 18 years old, or at least 16 years old and have:
    • Graduated from high school or been awarded a certificate equivalent to graduating from high school; or
    • Completed a formal vocational training program; or
    • Received a statement from school authorities agreeing with your preference for employment rather than continuing your education

For more information on qualifications please refer to OPM's Qualifications Standards.Education:A college or university degree generally must be from an accredited (or pre-accredited) college or university recognized by the U.S. Department of Education. For a list of schools which meet these criteria, please refer to Department of Education Accreditation page.
FOREIGN EDUCATION: Education completed in foreign colleges or universities may be used to meet the requirements. You must show proof the education credentials have been deemed to be at least equivalent to that gained in conventional U.S. education program. It is your responsibility to provide such evidence when applying. Click here (Section 3, Explanation of Terms) or here for Foreign Education Credentialing instructions.
We recommend choosing an evaluator from a member organization of one of the following national associations of credential evaluation services: National Association of Credential Evaluation Services (NACES) or Association of International Credentials Evaluators (AICE).Employment Type: OTHER

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