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Python Data Analyst Jobs in Philadelphia, PA (NOW HIRING)

SANS

Python Data Engineer

Philadelphia, PA · On-site

Write production-grade Python for data processing and integration between on-prem and cloud systems ... Track record owning delivery end to end, from data analysis and architecture through production ...

Inficare Technologies

Data Analyst

Malvern, PA · On-site

Job Title: Data Analyst Location: Malvern, PA * Engage with internal partners to understand ... Coding knowledge in SQL, Python, or the equivalent (SAS, R) * Data visualization using Tableau ...

kgs

Data Analyst

Philadelphia, PA · On-site

Compile, prepare, and analyze quantitative data using Excel, Python, R, and other analytical tools to support grant administration and program oversight. * Conduct both basic and complex statistical ...

kgs

Data Analyst

Philadelphia, PA · On-site

Compile, prepare, and analyze quantitative data using Excel, Python, R, and other analytical tools to support grant administration and program oversight. * Conduct both basic and complex statistical ...

ParetoHealth

Data Analyst

Philadelphia, PA · Remote

Experience using Python for analysis and data wrangling * Experience in data cleaning, validation, and exploratory analysis using large, complex datasets * Understanding of analytical methods ...

NAVA Software Solutions

Data Analyst

Malvern, PA · On-site

Data Analyst Engineer Location: Malvern, PA - Hybrid Duration: 6 -12 months Two Round Interview ... SQL Development experience (and/or Python development) (SAS or R could also be helpful) * Tableau ...

Vangard, Inc.

Data Analyst, Specialist

Malvern, PA · On-site

You will leverage SQL, Python, AWS, and modern analytics technologies to build scalable data products, automate reporting processes, and deliver actionable insights that support regulatory oversight ...

Vangard, Inc.

Data Analyst, Specialist

Malvern, PA · On-site

We are seeking a data visualization expert with a passion for transforming complex data into clear ... Experience in Python and advanced analytics * Demonstrated experience building executive-ready ...

AYR Global IT Solutions Inc

Python Developer

Philadelphia, PA · On-site

$50.75 - $70/hr

... Analysis and Design RDBMS and Object Relational Mapping Web Application Security Practices ... Python Data Structures Well Experienced in: Design Patterns Django Web Development Framework ...

Vangard, Inc.

Data Analyst, Specialist

Malvern, PA

Expertise in Python or R for data manipulation, automation and advanced analytics. * Hands-on experience with data visualization tools like Power BI, Tableau or Looker to create interactive reports.

Suvoda

Senior Data Analyst

Conshohocken, PA

$84K - $106K/yr

The Senior Data Analyst demonstrates analytical thinking and creative problem solving for business ... SQL (preferred), dbt, DAX, Python or equivalent. * Experience with Snowflake or an equivalent cloud ...

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All JobsPython Data Analyst JobsPython Data Analyst Jobs in Philadelphia, PA

Python Data Analyst information

See Philadelphia, PA salary details

$34.3K

$83.4K

$137.2K

How much do python data analyst jobs pay per year?

As of Jul 11, 2026, the average yearly pay for python data analyst in Philadelphia, PA is $83,391.00, according to ZipRecruiter salary data. Most workers in this role earn between $63,100.00 and $97,900.00 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.

Will AI replace a data analyst?

AI tools can automate routine data processing and analysis tasks, but the role of a data analyst involves interpreting insights, understanding business context, and communicating findings, which require human judgment. Data analysts who develop skills in programming, data visualization, and machine learning can adapt to new technologies and continue to add value in data-driven decision-making.

Is 40 too old to become a data analyst?

Age is not a barrier to becoming a data analyst; many professionals transition into the field later in life. Success depends on acquiring relevant skills such as SQL, Python, and data visualization, along with practical experience and certifications. Employers value diverse backgrounds and experience, making it possible to start a data analyst career at any age.

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 a high paying job?

Python Data Analysts are generally well-compensated due to their technical skills in programming, data manipulation, and analysis. Salaries vary based on experience, location, and industry, but proficiency in Python often leads to higher earning potential compared to many other entry-level roles in data analysis. Certifications and knowledge of related tools like SQL or machine learning can further increase salary prospects.

Is Python useful for data analysts?

Python is highly useful for data analysts because 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.
More about Python Data Analyst jobs
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Python Data Analyst jobs near you
Infographic showing various Python Data Analyst job openings in Philadelphia, PA as of July 2026, with employment types broken down into 1% Locum Tenens, 1% Internship, 75% Full Time, 18% Part Time, 1% Temporary, and 4% Contract. Highlights an 81% Physical, 7% Hybrid, and 12% Remote job distribution, with an average salary of $83,391 per year, or $40.1 per hour.

Python Data Engineer

SANS

Philadelphia, PA • On-site

Other

Posted 5 days ago

Job description


Client is placing a senior data integration consultant embedded at a financial services client. The consultant works onsite as part of the client's data engineering effort, integrating the client's systems and data sources with Client's Declarative Agentic Framework (DAF) and connected products.
This is delivery work, not advisory. The consultant owns the data pipelines, warehouse structures, and integration points that the deployment depends on, and is accountable for data quality and reliability in production.
What the Consultant Will Do

  • Design and build data integration pipelines connecting client source systems (reference data, pricing, transaction, custody, or similar) to client's AI's platform .
  • Own data warehouse and data lake architecture for the engagement, including ingestion, transformation, and data quality rules.
  • Work hands-on with ETL tooling (Informatica, Snowflake, or equivalent) and cloud data platforms (AWS or Azure).
  • Write production-grade Python for data processing and integration between on-prem and cloud systems.
  • Define data reconciliation and data lineage processes so the client can trust what the pipelines produce.
  • Coordinate with the client's data engineering, ops, and compliance stakeholders, and with client's AI's deployment team.
  • Document architecture decisions and integration patterns so the work is defensible and repeatable across future deployments.

Required Background

  • 10+ years in enterprise data architecture, data engineering, or solution architecture roles.
  • Direct experience in financial services, ideally capital markets, asset management, or securities operations. Candidate should recognize terms like reference data, corporate actions, and reconciliation without explanation.
  • Hands-on ETL and data warehousing expertise: Informatica, Snowflake , or comparable enterprise-grade tooling .
  • Production Python for data pipelines and integration work , not scripting on the side.
  • Experience with REST APIs, message queues (Kafka or similar), and containerized deployments (Docker).
  • Track record owning delivery end to end, from data analysis and architecture through production support, ideally with distributed or offshore team coordination.
  • Comfortable being the senior technical presence in the room with client stakeholders from day one. No ramp-up period.

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