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Weekend Python Data Analyst Jobs (NOW HIRING)

Swish Analytics

Sports Data Analyst

San Francisco, CA · On-site +1

Company Description Swish Analytics is a sports analytics, betting and fantasy startup building the ... Source origins of data inaccuracies through data pipeline dependencies and python code base

ConnectPrep

Data Analyst Internship

Washington, DC · Remote

SQL, Python data tools (Pandas, NumPy, or similar) * Building simple data pipelines or analysis scripts in Python * Excel & analysis skills * You are comfortable doing serious work in Excel ...

ConnectPrep

Data Analyst Internship

Washington, DC · On-site +1

SQL, Python data tools (Pandas, NumPy, or similar) * Building simple data pipelines or analysis scripts in Python * Excel & analysis skills * You are comfortable doing serious work in Excel ...

ConnectPrep

Data Analyst Internship

Washington, DC · On-site +1

SQL, Python data tools (Pandas, NumPy, or similar) * Building simple data pipelines or analysis scripts in Python * Excel & analysis skills * You are comfortable doing serious work in Excel ...

Excelhire

Data Analyst

Los Angeles, CA

$32/hr

Data Analyst - Join Our Team Data Analyst Los Angeles, CA | Full-Time | CTC, W2 Job Summary We are ... Basic knowledge of Python or R (preferred) Skills * Primary skills: Excel, SQL, data visualization ...

Hirekeyz Inc

Data QE

Tampa, FL · On-site

$108K - $129K/yr

Data Analyst who is ready to work on QE side with Java/Python * Data Engineers - Who is ready to do QE role with Java/Python * SQL query writing & programming (Java/Python) * Java/Python plays a role ...

NuView Analytics

Data Analyst

Denver, CO · Remote

$80K - $100K/yr

We do this in three ways - data analytics, data diligence, and fractional data science. Our clients ... R or Python experience a plus * Tableau, PowerBI, or Looker Proficiency including advanced ...

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How much do weekend python data analyst jobs pay per year?

As of Jul 15, 2026, the average yearly pay for weekend python data analyst in the United States is $82,640.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,500.00 and $97,000.00 per year, depending on experience, location, and employer.

What are some common challenges faced by Weekend Python Data Analysts, and how can they be managed?

Weekend Python Data Analysts often face challenges such as limited time to access stakeholders or full datasets, since many team members may not be available outside standard business hours. To manage these challenges, it’s important to communicate needs and data access requirements ahead of time, and to document findings thoroughly for seamless handovers. Being self-sufficient with Python tools and data wrangling is critical, as you may need to troubleshoot issues independently. Proactively setting clear goals for each shift can also help maximize productivity during weekend hours.

What are Weekend Python Data Analysts?

Weekend Python Data Analysts are professionals who work part-time or on weekends to analyze data using Python programming. They typically handle tasks such as cleaning data, performing statistical analyses, creating data visualizations, and generating reports. These analysts often support organizations that require flexible staffing or have projects that need attention outside of regular business hours. Their expertise in Python enables them to efficiently manipulate large datasets and extract actionable insights. This role is ideal for those seeking flexible work arrangements or supplementary income in the data analytics field.

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

To thrive as a Weekend Python Data Analyst, you need strong analytical skills, proficiency in Python programming, and a background in statistics or data science—often supported by a relevant degree or certification. Familiarity with data visualization tools (like Tableau or Power BI), SQL databases, and Python libraries such as Pandas and NumPy is typically expected. Excellent problem-solving, time management, and communication skills help you interpret data insights and present findings effectively during limited weekend hours. These skills ensure accurate data analysis, actionable recommendations, and efficient collaboration, even within a compressed work timeframe.

What is the difference between Weekend Python Data Analyst vs Weekend Data Scientist?

AspectWeekend Python Data AnalystWeekend Data Scientist
Required SkillsPython, data analysis, visualization, SQLPython, machine learning, statistical modeling, data analysis
CertificationsData analysis certifications, Python certificationsData science certifications, Python certifications
Work EnvironmentPart-time, project-based, remote or on-sitePart-time, project-based, remote or on-site
Industry UsageBusiness analytics, finance, marketingResearch, AI development, advanced analytics

Weekend Python Data Analysts focus on data cleaning, visualization, and basic analysis using Python, suitable for business insights. Weekend Data Scientists handle more complex modeling and machine learning tasks, often requiring advanced statistical skills. Both roles are part-time, flexible, and commonly used across industries, but Data Scientists typically require a deeper technical background.

What cities are hiring for Weekend Python Data Analyst jobs? Cities with the most Weekend Python Data Analyst job openings:
What are the most commonly searched types of Python Data Analyst jobs? The most popular types of Python Data Analyst jobs are:
What states have the most Weekend Python Data Analyst jobs? States with the most job openings for Weekend Python Data Analyst jobs include:
Weekend Python Data Analyst jobs near you
Sports Data Analyst

Sports Data Analyst

Swish Analytics

San Francisco, CA • On-site, Remote

Full-time

Re-posted 19 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.
Department Data Science Role NFL Team Locations San Francisco, CA - Remote Remote status Fully Remote

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