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

Vangard, Inc.

Data Analyst, Specialist

Malvern, PA

Advanced Python experience for analysis, modeling, and automation (e.g., pandas, NumPy, stats/ML libraries). * Proven data science skillset, including: * Driver and rootcause analysis * Timeseries ...

Vangard, Inc.

Data Analyst, Senior Specialist

Malvern, PA

$84K - $106K/yr

We are seeking an experienced data analyst to support the Flagship Client segment and the ... Demonstrates deep expertise in one or more technical domains (e.g., Python, advanced analytics ...

Vangard, Inc.

Data Analyst, Specialist

Malvern, PA

Build well-scoped models and analyses . Develop andvalidatemodels on defined problems such as ... Workingproficiencyin Python and SQL and comfort wrangling real, messy data. * Solid foundation in ...

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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 Aug 21, 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.

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.

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.

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.

Is Python good for data analysts?

Python is widely used by data analysts due to its simplicity, extensive libraries like pandas and NumPy, and strong community support. It enables efficient data manipulation, analysis, and visualization, making it a valuable skill for the role.
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Python Data Analyst jobs near you
Infographic showing various Python Data Analyst job openings in Philadelphia, PA as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $83,391 per year, or $40.1 per hour.

Data Analyst - Provider Data Management

PurpleLab Inc

Wayne, PA • On-site

$110K - $130K/yr

Full-time

Posted 7 days ago

Job description

Description:

The Data Analyst – Provider Data Management is responsible for driving our mission of transforming healthcare insights through advanced data solutions. In this role, you’ll serve as our Provider Data Subject Matter Expert (SME) while managing, validating, and enhancing our extensive healthcare provider datasets. This position is ideal for professionals who excel at identifying patterns, spotting inconsistencies, and ensuring data quality across complex healthcare information systems.


DUTIES AND RESPONSIBILITIES:

Provider Data Excellence

· Serve as the company's Subject Matter Expert in healthcare provider information, managing a comprehensive dataset of over 10 million practitioners and healthcare organizations.

· Apply your healthcare provider knowledge to identify and resolve data discrepancies, ensuring accuracy and completeness of provider profiles.

· Develop and maintain data quality standards specific to healthcare provider information.

Strategic Data Analysis & Insights

· Lead comprehensive analysis and integration of healthcare datasets from diverse sources including claims data, public records, and third-party vendors.

· Transform raw provider data into meaningful insights that drive business decisions.

· Identify trends and anomalies in provider data that impact healthcare operations.

Data Operations & Quality Assurance

· Monitor end-to-end data workflows for the ingestion, processing, exception resolution, and delivery of PurpleLab’s provider data assets.

· Apply meticulous attention to detail when reviewing data for accuracy, completeness, and consistency.

· Collaborate with product management and technical teams to identify data quality issues and implement solutions.

· Contribute to the development of data validation rules and quality control processes.

Industry Landscape & Innovation

· Stay current with healthcare industry trends including provider network changes, mergers & acquisitions, and regulatory updates.

· Maintain awareness of evolving provider data sources, compliance standards, and best practices in healthcare data management.

· Share insights about provider data landscape with cross-functional teams.

· Perform other duties as assigned to support business needs and company objectives.

Requirements:

· Bachelor’s degree in Healthcare Management, Data Science, or a related field required.

· 2+ years of healthcare data management experience, preferably with a focus on provider data management is required.

· In-depth knowledge of healthcare markets and provider information, including licensing & credentialing, provider networks and affiliations, and claims/revenue cycle is required.

· Proficiency with standard data management tools and IDEs, including writing SQL queries is required.

· Certifications in data management or healthcare analytics is preferred.

· Experience with cloud platform (AWS or Google Cloud) and data scripting (Python/R) is preferred.

· Experience in healthcare technology startup environment is preferred.



*Please do not contact human resources, hiring managers or employees directly regarding this position. All communication should go through application portal. Applicants who reach out to individuals outside the designated contact will not receive a response.