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Freelance Python Data Analysis Jobs (NOW HIRING)

Staffingine LLC

Senior Data Scientist

Los Angeles, CA · On-site

... Python Lead data science projects from concept to implementation ensuring timely delivery and quality outcomes * Perform exploratory data analysis to identify patterns trends and opportunities for ...

Swish Analytics

Sports Data Analyst

San Francisco, CA · On-site +1

Data Extraction, Wrangling and Analysis in Python * Strong SQL querying skills * Attention to detail Preferred: * Strong Python data management programming skills * Data Visualization experience with ...

DataAnnotation

$60/hr

... data analysis and visualization. Your work directly contributes to refining intelligent systems ... JavaScript, TypeScript, Python, C, C#, C++, React, Go, Java, or Swift. Excellent writing and ...

Acunor Infotech

Data Product Analyst

Manhattan, NY · On-site +1

Strong SQL skills with working knowledge of Python * Experience with QA/UAT and data validation ... reporting and business analysis * Strong stakeholder communication and cross-functional ...

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How much do freelance python data analysis jobs pay per hour?

As of May 29, 2026, the average hourly pay for freelance python data analysis in the United States is $58.62, according to ZipRecruiter salary data. Most workers in this role earn between $48.32 and $66.59 per hour, depending on experience, location, and employer.

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

To thrive as a Freelance Python Data Analyst, you need strong analytical skills, proficiency in Python programming, and a solid understanding of statistics and data manipulation, often backed by a relevant degree or proven portfolio. Experience with tools such as Pandas, NumPy, Jupyter Notebooks, and data visualization libraries like Matplotlib or Seaborn is typically required. Excellent problem-solving abilities, communication skills, and the ability to manage projects independently distinguish top performers in this role. These skills enable analysts to deliver actionable insights, meet client expectations, and maintain a successful freelance business.

What are some common challenges freelance Python data analysts face when working with clients remotely?

Freelance Python data analysts often encounter challenges such as clarifying project requirements, managing client expectations about deliverables, and ensuring timely communication across different time zones. Working remotely can also mean troubleshooting data access or security issues, especially if clients have strict data privacy policies. Building trust through regular updates and transparent reporting is key to successful collaborations in this role.

What is freelance Python data analysis?

Freelance Python data analysis involves using the Python programming language to analyze and interpret data for clients on a project or contract basis. Freelancers in this field typically work with datasets to extract insights, visualize results, and help businesses make data-driven decisions. They often use libraries such as pandas, NumPy, and matplotlib, and may work across industries like finance, marketing, healthcare, and technology. Freelancers enjoy flexibility in choosing their projects and clients, and often work remotely.
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Freelance Python Data Analysis jobs near you
Infographic showing various Freelance Python Data Analysis job openings in the United States as of May 2026, with employment types broken down into 72% Full Time, 14% Part Time, and 14% Contract. Highlights an 100% In-person job distribution, with an average salary of $121,932 per year, or $58.6 per hour.
Sports Data Analyst

Sports Data Analyst

Swish Analytics

San Francisco, CA

Full-time

Posted 2 days ago

Job description

Company Description

Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of predictive sports analytics data products. We believe that oddsmaking is a challenge rooted in engineering, mathematics, and sports betting expertise; not intuition. We're looking for team-oriented individuals with an authentic passion for accurate and predictive real-time data who can execute in a fast-paced, creative, and continually-evolving environment without sacrificing technical excellence. Our challenges are unique, so we hope you are comfortable in uncharted territory and passionate about building systems to support products across a variety of industries and consumer/enterprise clients.

Duties:

  • Work closely with Data Scientists and Engineers to diagnose and treat data pipeline integrity issues

  • Detect data inaccuracies such as missing, out of range or otherwise incorrect on-field data

  • Source origins of data inaccuracies through data pipeline dependencies and python code base

  • Define data validation tests to flag future game errors

  • Research accurate roster active statuses, primary positions and game participation

  • Validate data changes after logic updates

  • Production model feature deep dives to explain project market lines

  • Clearly document findings

  • Develop intimate familiarity with existing databases and construct metadata references

  • With guidance, support lead Data Scientists in feature development and model analysis

Requirements:

  • Bachelor's Degree in Computer Science, Data Science or similar major

  • Minimum of 1 year of experience in football data analysis

  • Deep knowledge of football, basketball or baseball; including roster compositions of professional and college teams, general gameplay strategies, and typical in-game scenarios

  • Data Extraction, Wrangling and Analysis in Python

  • Strong SQL querying skills

  • Attention to detail

Preferred:

  • Strong Python data management programming skills

  • Data Visualization experience with a user application like Streamlit

  • Deep knowledge of a second sport including football, basketball, baseball, hockey or tennis

  • Exposure to the data science process and tech stack

  • Anomaly Detection Techniques

Swish Analytics is an Equal Opportunity Employer. All candidates who meet the qualifications will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, pregnancy status, genetic, military, veteran status, marital status, or any other characteristic protected by law. The position responsibilities are not limited to the responsibilities outlined above and are subject to change. At the employer’s discretion, this position may require successful completion of background and reference checks.