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Python Data Analysis Internship Jobs in Tennessee

Spend Analysis & Insight Generation: Analyze purchasing and spend data across suppliers, categories ... Exposure to R or Python is a nice-to-have, not a requirement. Communication & Presentation:

Statistical Analysis and Computational Support * Perform statistical analyses and exploratory data analyses using R, Python, SQL, and/or related analytical platforms. * Support biomarker discovery ...

Work with Python, SAS, and other analytic computing environments to handle big data. * Research and Develop : Create innovative statistical models for data analysis. * Communicate Insights : Present ...

Query and manipulate data using SQL, Python, and similar tools to support both recurring reporting and ad-hoc analysis. Build customized analyses and reports across revenue, consumption and marketing ...

Work with Python, SAS, and other analytic computing environments to handle big data. * Research and Develop : Create innovative statistical models for data analysis. * Communicate Insights : Present ...

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Python Data Analysis Internship information

What is a Python Data Analysis Internship?

A Python Data Analysis Internship is a temporary position, often for students or recent graduates, that provides hands-on experience in analyzing data using the Python programming language. Interns typically assist with collecting, cleaning, and interpreting large datasets, using Python libraries such as pandas, NumPy, and matplotlib. The internship is designed to help participants develop practical skills in data manipulation, statistical analysis, and data visualization. It is a great way to gain real-world experience in data science and analytics while building a professional network.

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

To thrive as a Python Data Analysis Intern, you need a solid understanding of statistics, data manipulation, and Python programming, often supported by relevant coursework or projects. Familiarity with tools such as pandas, NumPy, Jupyter Notebook, and data visualization libraries like matplotlib or seaborn is typically required. Strong analytical thinking, attention to detail, and effective communication skills help interns interpret data and share insights clearly with team members. These skills enable interns to extract actionable insights from complex datasets and effectively contribute to data-driven decision making.

What is the difference between Python Data Analysis Internship vs Data Analyst?

AspectPython Data Analysis InternshipData Analyst
Required SkillsPython, data analysis, basic statisticsData analysis, SQL, Excel, Python (optional)
Work EnvironmentInternship setting, learning-focusedFull-time or part-time professional role
Experience LevelEntry-level, internshipEntry to mid-level professional
Industry UsageInternship programs, entry rolesBusiness, finance, tech, healthcare

While a Python Data Analysis Internship focuses on gaining hands-on experience with Python and data analysis tools in an internship setting, a Data Analyst role involves applying these skills professionally to analyze data, generate reports, and support decision-making in various industries.

What types of projects and tasks can I expect to work on during a Python Data Analysis Internship?

As a Python Data Analysis intern, you can typically expect to work on projects involving data collection, cleaning, and exploration using Python libraries such as Pandas and NumPy. Your daily tasks may include writing scripts to automate data processing, creating visualizations with tools like Matplotlib or Seaborn, and assisting in preparing reports or presentations based on your findings. Interns often collaborate with data scientists, analysts, and sometimes other departments to support ongoing projects and gain exposure to real-world data challenges. This hands-on experience is valuable for building both technical skills and an understanding of how data-driven decisions are made in a professional environment.
What are the most commonly searched types of Python Data Analysis jobs in Tennessee? The most popular types of Python Data Analysis jobs in Tennessee are:
What are popular job titles related to Python Data Analysis Internship jobs in Tennessee? For Python Data Analysis Internship jobs in Tennessee, the most frequently searched job titles are:
What job categories do people searching Python Data Analysis Internship jobs in Tennessee look for? The top searched job categories for Python Data Analysis Internship jobs in Tennessee are:
Analyst, Data & Insights

Analyst, Data & Insights

omnia

Franklin, TN • On-site

Other

Posted 17 days ago


Job description

Analyst, Data & Insights

Location: Franklin, TN – In Office Only

Candidates must be legally authorized to work in the U.S. without sponsorship, now and in the future.

Job Description

OMNIA Partners is seeking a polished and detail-oriented Analyst, Data & Insights to support reporting and spend analysis for one of our largest and most visible customer relationships. This role is ideal for a mid-career analyst who combines solid technical reporting skills with strong communication and presentation ability, and who takes pride in delivering clean, accurate, decision-ready analysis to a sophisticated and demanding audience.

In this role, you will be the analytical backbone behind a strategic customer account—turning purchasing and spend data into clear insights, recurring reports, and business review materials that the customer trusts. You will partner closely with internal business and operations leaders and serve as a key contributor to how OMNIA presents value and performance to this customer.

If you are an analyst who is equally comfortable writing a SQL query and standing in front of a critical stakeholder to walk them through the numbers, we encourage you to apply.

Core Responsibilities

Customer-Facing Reporting & Presentation: Prepare and deliver clear, professional, executive-ready spend analyses, recurring reports, and business review materials for a strategic customer account. Present findings directly to a detail-oriented customer with poise and credibility, anticipate the questions a critical stakeholder will ask, and respond to ad hoc data requests with accuracy, responsiveness, and a high standard of polish. This is the most important dimension of the role.

Spend Analysis & Insight Generation: Analyze purchasing and spend data across suppliers, categories, and time periods to surface contract utilization, savings, trends, and opportunities. Move beyond raw numbers to provide context and a clear narrative that helps the customer understand performance and act on it.

Dashboard & Report Development: Build, maintain, and continuously refine dashboards and recurring reporting in Tableau that are accurate, easy to read, and aligned to what the customer actually cares about. Ensure reporting assets are reliable, repeatable, and well-organized over time.

Data Integration & SQL Execution: Pull and combine data from Snowflake and other internal and external systems into clean, analysis-ready datasets. Write accurate, reliable SQL and reconcile data across sources so that the numbers presented externally hold up to scrutiny.

Data Quality & Accuracy: Validate outputs, investigate discrepancies, and ensure the figures shared with the customer are trustworthy. Identify the root cause of data issues and partner with internal teams to resolve them before they reach the customer.

Process Improvement & Work Management: Streamline recurring reporting to reduce manual effort and improve turnaround. Manage multiple concurrent requests with disciplined prioritization, clear communication of timelines, and consistent, on-time delivery.

Qualifications and Characteristics for Success

Education: Bachelor's degree in Data Science, Statistics, Analytics, Business, Finance, or a related field. An advanced degree is a plus but not required.

Experience: 3–6 years of experience in data analysis, reporting, or business intelligence, including experience preparing and presenting analysis to business stakeholders or external customers. Experience in a client-facing, account-support, or customer reporting capacity is strongly preferred.

Technical Skills: Solid working proficiency in SQL and Snowflake is required, along with strong skills in Tableau for dashboard and report development. Advanced Excel skills and strong PowerPoint skills are essential, as much of this role's output is delivered through spreadsheets and presentations. Comfort working in Figma is preferred: while this is not a design role, the successful candidate will navigate existing Figma files to make routine design updates and export assets that feed into customer-facing reporting and presentation materials.  Familiarity with Salesforce reporting and data structures is helpful or can be developed quickly. Exposure to R or Python is a nice-to-have, not a requirement.

Communication & Presentation: Exceptional communication and presentation skills are essential. The successful candidate is comfortable and credible presenting data to a critical, detail-oriented audience, can explain technical findings to non-technical stakeholders in plain language, and consistently produces clean, professional, well-organized deliverables. Composure and professionalism under questioning are key to success.

Attention to Detail & Professional Characteristics: Exceptional attention to detail, accountability, and a customer-service orientation are critical. The Analyst must be self-directed, dependable, relentlessly curious, responsive to shifting priorities, and motivated to deliver high-quality, trustworthy work that reflects well on OMNIA in front of an important customer.