ZipRecruiter

Log In

1

Data Science Analytics Jobs in Pennsylvania (NOW HIRING)

Transunion

Senior Data Analyst

Crum Lynne, PA

$90K - $150K/yr

You will be working with other Data Analytics Team members as well as Engineers and Data Scientists to help improve automation algorithms and leveraging big data to arrive at the most up to date ...

ICON

Director, Feasibility Data Science

Blue Bell, PA · On-site

In this role, you will lead the design and delivery of advanced analytics and data science capabilities that support clinical trial feasibility, protocol optimization, study planning, country and ...

Ntta

$97K - $128K/yr

Bachelor's degree in Business or Computer Science, Analytics, Information Technology, Engineering, Management, or related field. * 7+ years of experience in data analytics, operations, or business ...

previous page

Showing results 41-60

All JobsData Science Analytics JobsData Science Analytics Jobs in Pennsylvania

Data Science Analytics information

See Pennsylvania salary details

$24

$54

$94

How much do data science analytics jobs pay per hour?

As of Aug 23, 2026, the average hourly pay for data science analytics in Pennsylvania is $54.88, according to ZipRecruiter salary data. Most workers in this role earn between $44.09 and $62.16 per hour, depending on experience, location, and employer.

What is data science analytics?

Data science analytics is the process of extracting insights and knowledge from data using statistical, mathematical, and computational techniques. It involves collecting, cleaning, analyzing, and visualizing data to help organizations make informed decisions. Professionals in this field use tools like Python, R, and SQL to interpret complex data sets, build predictive models, and identify trends or patterns. Data science analytics plays a key role in industries such as finance, healthcare, retail, and technology, enabling businesses to optimize operations and improve outcomes.

What are the key skills and qualifications needed to thrive as a data science analytics professional?

To thrive in Data Science Analytics, a strong background in statistics, data modeling, and programming (often with a degree in computer science, mathematics, or a related field) is essential. Familiarity with tools such as Python, R, SQL, and data visualization platforms like Tableau or Power BI, as well as knowledge of machine learning libraries, is typically required. Critical thinking, problem-solving, and effective communication skills help professionals translate complex data insights into actionable business strategies. These competencies are crucial for extracting meaningful information from data and driving informed decision-making within organizations.

How do data science analytics professionals typically collaborate with other departments within an organization?

Data science analytics professionals often work closely with teams across the organization, such as marketing, finance, product development, and IT. Their role involves understanding business needs, gathering requirements, and translating complex data findings into actionable insights for non-technical stakeholders. Effective communication and teamwork are essential, as data scientists may participate in cross-functional meetings, present their analyses, and tailor their recommendations to support strategic decision-making. This collaborative approach not only enhances the impact of analytics projects but also fosters continuous learning and innovation within the organization.

What is the difference between Data Science Analytics vs Data Analyst?

AspectData Science AnalyticsData Analyst
Required CredentialsDegree in Data Science, Statistics, or related fields; programming skillsDegree in Statistics, Mathematics, or related fields; proficiency in Excel and SQL
Work EnvironmentOften involves complex modeling, machine learning, and predictive analyticsFocuses on data cleaning, reporting, and visualization
Employer & Industry UsageTech companies, finance, healthcare, and research institutionsBusiness, marketing, finance, and operations across various industries

Data Science Analytics and Data Analysts both work with data, but Data Science Analytics typically involves advanced modeling and predictive techniques, while Data Analysts focus on data reporting and visualization. The roles often overlap, but Data Science Analytics requires more technical skills and a deeper understanding of algorithms.

What can I do with data science analytics?

Data science analytics involves analyzing large datasets to extract insights, support decision-making, and solve complex problems. Professionals in this field use tools like Python, R, and SQL, and often work in industries such as finance, healthcare, or marketing to develop predictive models and visualize data. Skills in statistics, machine learning, and data visualization are essential for success in this role.

What are the most commonly searched types of Data Science Analytics jobs in Pennsylvania?

The most popular types of Data Science Analytics jobs in Pennsylvania are:

What are popular job titles related to Data Science Analytics jobs in Pennsylvania?

For Data Science Analytics jobs in Pennsylvania, the most frequently searched job titles are:

What job categories do people searching Data Science Analytics jobs in Pennsylvania look for?

The top searched job categories for Data Science Analytics jobs in Pennsylvania are:

Data Science Analytics jobs near you
Infographic showing various Data Science Analytics job openings in Pennsylvania as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 17% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $114,147 per year, or $54.9 per hour.

AI Data Science Expert - Remote

YO AI Labs

Philadelphia, PA • Remote

$100 - $200/hr

Part-time

Posted 12 days ago

Job description

Job Title: AI Data Science Domain Expert

Job Type: Contractor (Part-Time)
Location: Remote

Job Overview

We are seeking experienced AI Data Science Domain Experts to contribute their expertise to an innovative project focused on advancing next-generation AI systems. In this role, you will review, evaluate, and refine AI-generated technical and analytical content to improve model accuracy, reasoning, and overall performance. No prior AI experience is required—your data science expertise, analytical thinking, and communication skills are what matter most.

Key Responsibilities
  • Review, edit, and refine AI-generated content for accuracy, clarity, and technical relevance.
  • Develop, optimize, and evaluate prompts to improve AI model performance.
  • Conduct rubric-based assessments of AI outputs and provide structured feedback.
  • Perform independent research and fact-checking to validate technical information.
  • Annotate data and support quality assurance initiatives for AI training.
  • Interpret complex datasets and prepare clear technical reports and summaries.
  • Collaborate remotely with project teams to improve AI models and workflows.
Required Skills
  • Critical Thinking
  • Analytical Reasoning
  • Prompt Engineering
  • AI Output Evaluation
  • Quality Assurance
  • Technical Documentation
  • Technical & Report Writing
  • Content Review & Editing
  • Data Annotation
  • Data Interpretation
  • Fact Checking
  • Independent Research
  • Problem-Solving
  • Attention to Detail
Preferred Qualifications
  • 3+ years of experience in Data Science, Machine Learning, Applied AI, Statistics, Quantitative Analytics, or Data Analytics.
  • Experience producing or reviewing research papers, analytical reports, technical documentation, experiment summaries, or data-driven recommendations.
  • Strong analytical reasoning, critical thinking, and written communication skills.
  • Experience with data annotation, content review, or rubric-based evaluation is preferred.
  • Familiarity with prompt engineering, AI output evaluation, fact-checking, or RLHF is a plus.
  • Master's, MBA, PhD, or other advanced degree is preferred.