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Python Data Analyst Jobs in Richmond, VA (NOW HIRING)

Principal Data Analyst At Capital One, data is at the center of everything we do. When we launched ... Scripting experience in (Python, R, Spark, and SQL) * Strong desire and experience with data in ...

Principal Data Analyst At Capital One, data is at the center of everything we do. When we launched ... Scripting experience in (Python, R, Spark, and SQL) * Strong desire and experience with data in ...

Sr. Data Analyst@ Richmond, VA

Richmond, VA · On-site

$85K - $107K/yr

Role Info: Hands on Data Analyst role with good SQL & Python background. Supporting business resolutions on technical on analytical parameters and data analysis Top Skills: 10+ Yrs of exp is a must ...

Senior Data Analyst

Richmond, VA · On-site

$85K - $107K/yr

Senior Data Analyst At Capital One, data is at the center of everything we do. When we launched as ... Scripting experience in (Python, R, Spark, and SQL) * Strong desire and experience with data in ...

Senior Data Analyst

Richmond, VA · On-site

$85K - $107K/yr

Senior Data Analyst At Capital One, data is at the center of everything we do. When we launched as ... Scripting experience in (Python, R, Spark, and SQL) * Strong desire and experience with data in ...

Experience Requirements * 80% SQL (database program languages), 20% python (not required) * Data analysis, manipulation and exploration, problem solving * Dashboard creation is nice to have, not need ...

Senior Data Analyst-Tech Analytics

Richmond, VA · On-site

$85K - $107K/yr

Senior Data Analyst-Tech Analytics At Capital One, data is at the center of everything we do. When ... Scripting experience in (Python, R, Spark, and SQL) * Strong desire and experience with data in ...

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Python Data Analyst information

See Richmond, VA salary details

$33.6K

$81.8K

$134.6K

How much do python data analyst jobs pay per year?

As of Jun 24, 2026, the average yearly pay for python data analyst in Richmond, VA is $81,783.00, according to ZipRecruiter salary data. Most workers in this role earn between $61,900.00 and $96,000.00 per year, depending on experience, location, and employer.

What does a Python Data Analyst do?

A Python Data Analyst leverages the Python programming language to collect, process, and analyze large sets of data. They use tools and libraries like Pandas, NumPy, and Matplotlib to clean data, perform statistical analysis, and create visualizations that help organizations make data-driven decisions. Their role often involves extracting insights from complex datasets, automating data workflows, and communicating findings to stakeholders through reports or dashboards. Python Data Analysts play a crucial part in turning raw data into actionable business intelligence.

How do Python Data Analysts typically collaborate with other departments within an organization?

Python Data Analysts often work closely with teams such as marketing, finance, and product development to provide data-driven insights that inform business decisions. They regularly participate in cross-functional meetings to understand departmental objectives, gather requirements for data analysis, and present their findings in an accessible manner. Effective communication and the ability to translate technical results into actionable recommendations are essential, as analysts often act as a bridge between technical data and non-technical stakeholders.

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

AspectPython Data AnalystData Scientist
Required SkillsPython, SQL, data visualization, statistical analysisPython, R, machine learning, statistical modeling
Work EnvironmentBusiness analytics, reporting, data cleaningAdvanced modeling, predictive analytics, research
Industry UsageFinance, marketing, healthcare, retailTech, finance, research, AI development

While both roles require Python and data analysis skills, Data Scientists typically engage in more complex modeling and machine learning, whereas Python Data Analysts focus on data cleaning, visualization, and reporting to support business decisions.

What Does a Python Data Analyst Do?

As a Python data analyst, you use the Python programming language to develop tools for data mining, analysis, and data visualization. You typically develop a script to meet the specific data needs of your client or employer. Then, you test your code and perform debugging duties before deploying it in a live environment. Some data analysts also have algorithm creation responsibilities. In this case, after creating and testing an algorithm, you use Python with your algorithm to interpret data. You also develop reports to show to your clients or employers, and you may code a web app or interface that clients can use to visualize data sets.

Are Python coders still in demand?

Python data analysts are currently in high demand due to the language's versatility in data analysis, machine learning, and automation. Skills in libraries like Pandas, NumPy, and experience with data visualization tools increase employability across various industries.

Is 40 too old to become a data analyst?

Age is not a barrier to becoming a data analyst. Many professionals successfully transition into data analysis at various ages by acquiring skills in programming languages like Python or SQL, and gaining experience with data visualization tools. Employers value skills and experience over age, and continuous learning can help you stay competitive in the field.

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

To thrive as a Python Data Analyst, you need strong analytical skills, a solid grasp of statistics, and proficiency in Python programming, often supported by a degree in data science, mathematics, or a related field. Familiarity with data analysis libraries like pandas and NumPy, visualization tools such as Matplotlib or Seaborn, and experience with data querying languages like SQL are typically required. Attention to detail, critical thinking, and effective communication help you derive insights and present findings clearly to stakeholders. These skills and qualities are vital for transforming raw data into actionable business intelligence and supporting data-driven decision-making.

Is Python useful for data analysts?

Python is highly useful for data analysts as it offers powerful libraries like Pandas, NumPy, and Matplotlib for data manipulation, analysis, and visualization. It is widely used in the industry for automating tasks, building data pipelines, and performing statistical analysis, making it a valuable skill for the role.

Will AI replace data analysts?

AI is transforming the role of data analysts by automating routine tasks such as data cleaning and basic analysis, but it is unlikely to fully replace them. Data analysts are needed to interpret complex insights, make strategic decisions, and develop models that require domain expertise and critical thinking. Skills in programming, data visualization, and understanding AI tools remain valuable in this evolving field.
What are popular job titles related to Python Data Analyst jobs in Richmond, VA? For Python Data Analyst jobs in Richmond, VA, the most frequently searched job titles are:
What job categories do people searching Python Data Analyst jobs in Richmond, VA look for? The top searched job categories for Python Data Analyst jobs in Richmond, VA are:
Infographic showing various Python Data Analyst job openings in Richmond, VA as of June 2026, with employment types broken down into 3% As Needed, 33% Full Time, 53% Part Time, 10% Contract, and 1% Nights. Highlights an 82% Physical, 7% Hybrid, and 11% Remote job distribution, with an average salary of $81,783 per year, or $39.3 per hour.

Full-time

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Job description

Responsibilities:
- Collaborate with internal teams to understand data needs and objectives.
- Extract, clean, and transform data from diverse sources for analysis.
- Perform data analysis to identify trends, patterns, and anomalies.
- Examine data quality, applications, and functions to ensure accurate migration.
- Produce output and sustain operation of data migration processes.
- Research new data sources and analytical tools for improved migration strategies.
- Contribute to new product development and enhancements in data delivery and presentation.
- Interpret data, analyze results using statistical techniques, and provide ongoing reports.
- Identify, analyze, and interpret trends or patterns in complex data sets.
- Generate visualizations and reports for stakeholders.
- Develop and implement databases, data collection systems, data analytics, and other strategies that optimize statistical efficiency and quality.
- Acquire data from primary or secondary data sources and maintain databases/data systems.
- Collaborate with the LEAMS team to perform a proper audit of active files during the migration.
Qualifications:
- Proven experience as a Data Analyst or related role.
- Technical expertise regarding data models, database design, data mining, and segmentation techniques.
- Strong knowledge of and experience with reporting packages and databases (SQL, etc.).
- Proficient in programming languages (Python, R, etc.) is a plus.
- Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.
- Adept at queries, report writing, and presenting findings.
- Strong knowledge in Microsoft Office with emphasis on Microsoft Excel.