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Data Science R Jobs in Pennsylvania (NOW HIRING)

Dlapiper

Data Scientist

Philadelphia, PA · On-site +1

Python, R, SQL, SAS, NLTK, Scikit-Learn, Excel, Tableau, Power BI, and Jupyter; Basic data science concepts: probability, statistics, hypothesis testing, machine learning, natural language processing ...

Munich Re

Data Scientist

Philadelphia, PA · On-site +1

Join our dynamic, centralized Data Science team as we execute our AI/ML roadmap! We focus on ... Proficiency in statistical programming languages such as R, Python, SAS, or similar, alongside ...

Bread Financial

Lead Data Scientist

Chadds Ford, PA · On-site +1

$144K - $250K/yr

Bachelor's Degree in Statistics, Mathematics, Engineering, Data Science, Computer Science, or ... R Statistics * Statistical Analysis * Statistics * Time Series Analysis * Cloud Environment

Eastern University

Adjunct Faculty- Data Science

PA · On-site +1

Data Science - (College of Health and Sciences) Opening Date: 01/25/2024 Join our vibrant community ... Python * R and Tidyverse * Databases and database management with SQL * Business analytics

Havis Inc

Data Scientist

Warminster, PA · On-site

... R, LLM, and related technologies. * Build, maintain, and optimize ETL/ELT pipelines that ingest ... Bachelor's degree in Data Science, Computer Science, Information Systems, Finance, Quantitative ...

System One

Research Data Scientist

Pittsburgh, PA · On-site

D. preferred) in Data Science, Statistics, Computer Science, or a related quantitative field * 3+ ... Proficiency in programming languages such as Python or R * Experience working with large, complex ...

System One

Research Data Scientist

Pittsburgh, PA · On-site

D. preferred) in Data Science, Statistics, Computer Science, or a related quantitative field * 3+ ... Proficiency in programming languages such as Python or R * Experience working with large, complex ...

System One

Research Data Scientist

Pittsburgh, PA · On-site

D. preferred) in Data Science, Statistics, Computer Science, or a related quantitative field * 3+ ... Proficiency in programming languages such as Python or R * Experience working with large, complex ...

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Data Science R information

What is a Data Science R?

A Data Science R job involves using the R programming language for data analysis, statistical modeling, and machine learning. Professionals in this role work with large datasets, clean and preprocess data, apply predictive modeling techniques, and visualize insights. They often use libraries like ggplot2, dplyr, and caret to manipulate data and build models. This role is common in industries such as finance, healthcare, and marketing, where data-driven decision-making is essential. Strong statistical knowledge, programming skills, and domain expertise are key to success in this position.

What does a Data Science R do?

In most organizations, Data Science R professionals spend their days gathering and cleaning data, performing exploratory data analysis with R, building and evaluating predictive models, and generating data visualizations to communicate results. They often meet with cross-functional teams to understand business needs, translate them into data projects, and present key findings. Additionally, they may write reproducible R scripts, maintain data pipelines, and document their methodologies. Collaboration, experimentation, and clear communication are integral parts of the role, enabling solutions that directly impact business outcomes.

What are the key skills and qualifications needed to thrive in the Data Science R position, and why are they important?

To thrive as a Data Science R professional, you need solid expertise in statistics, machine learning, and programming in R, often supported by a degree in data science, statistics, or a related field. Experience with R-based data analysis libraries, visualization tools like ggplot2, and familiarity with databases or cloud platforms is typically expected; certifications in data science or R programming can be advantageous. Strong problem-solving abilities, attention to detail, and effective communication with stakeholders help distinguish top performers in this role. These skills are essential for delivering actionable insights from complex datasets and driving data-informed decision-making within organizations.

Is R useful for data science?

Data Science R is a popular programming language used for statistical analysis, data visualization, and machine learning. It offers extensive libraries and tools that are widely adopted in data science workflows, making it a valuable skill for data analysts and data scientists. Proficiency in R can enhance data manipulation, modeling, and reporting capabilities in data science roles.

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

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

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

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

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

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

What cities in Pennsylvania are hiring for Data Science R jobs?

Cities in Pennsylvania with the most Data Science R job openings:

Data Science R jobs near you
Infographic showing various Data Science R 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.

Principal Scientist, Data Science - R&D DDSAI - Therapeutics Development & Supply (TDS)

Spring House, PA • On-site

Scorpion Therapeutics
51 - 200 employees
Learn more about Scorpion Therapeuticsexternal

Other

PTO

Posted 12 days ago

Job description

Position Summary:

Data Scientist – Data Engineer (R&D DDSAI – Therapeutics Development & Supply, TDS). Design, build, and optimize data capture, processing, and storage solutions enabling advanced analytics, digital transformation, and AI/ML across the development-to-supply continuum.

Key Responsibilities:
  • Design, build, and maintain scalable data pipelines integrating TDS data from lab systems, MES, clinical supply, quality systems, and external partners.
  • Create/optimize structured and unstructured data flows using Python, R, SQL, DBT, cloud services, and modern engineering tools.
  • Build and maintain TDS data repositories; implement enterprise data models.
  • Ensure AI/ML readiness (well-structured, versioned, traceable, semantically aligned data).
  • Partner with data scientists and domain experts to define data products and engineering requirements.
  • Implement semantic/knowledge graph models and future-proof architectures.
  • Establish data quality/performance standards; define KPIs (accuracy, completeness, consistency).
  • Apply data versioning and lineage for compliance, traceability, and audit readiness; follow DevOps, documentation, and code versioning best practices.
Qualifications:Required:
  • Advanced degree (Engineering/Data Science/Life Sciences/CS or related); advanced degree preferred.
  • 3+ years data engineering (data modeling/database design), preferably in scientific/manufacturing/healthcare.
  • Proficiency: Python, R, SQL; cloud architectures (e.g., AWS, Snowflake, Redshift).
  • Experience with NoSQL and graph databases.
  • Strong analytical/problem-solving and stakeholder management; translate needs into requirements.
Preferred:
  • Regulated/standards-driven data (CDISC, HL7, FHIR, OMOP, DICOM, manufacturing/quality).
  • High-dimensional data (imaging/sensor).
  • Knowledge of MLOps/model deployment workflows.
  • Manufacturing systems (MES), lab information systems, or industrial data systems.
  • Knowledge graph architecture experience.
Required Skills:
  • Advanced Analytics
  • Data Analysis
  • Data Quality
  • Data Reporting
  • Data Science
  • Data Visualization
  • Digital Fluency
  • Critical Thinking
  • Technical Credibility
  • Workflow Analysis
  • Data Privacy Standards
Preferred Skills:
  • Coaching
  • Data Savvy
  • Econometric Models
  • Organizing
  • Process Improvements
  • Strategic Thinking
Benefits (time off):
  • Vacation (120 hrs/yr)
  • Sick time (40 hrs/yr; CO/Washington varies)
  • Holiday pay incl. Floating Holidays (13 days/yr)
  • Work/Personal/Family Time (up to 40 hrs/yr)
  • Parental Leave (480 hrs/yr)
  • Bereavement Leave (240 hrs/yr immediate family; 40 hrs extended family)
  • Caregiver Leave (80 hrs in 52-week period)
  • Volunteer Leave (32 hrs/yr)
  • Military Spouse Time-Off (80 hrs/yr)
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