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Postdoc Data Science Remote Jobs in Philadelphia, PA

Data Engineer

West Chester, PA · Remote

$108K - $130K/yr

Where You'll Work This role is remote; job seekers must reside in one of the following states to be ... Create data products for analytics and data science teams to improve their productivity and ...

Identify and articulate meta-level criteria for evaluating the robustness, validity, and scientific ... Experience supervising PhD students, postdoctoral researchers , or equivalent research leadership ...

Science Educator

Wilmington, DE · On-site +1

$68K/yr

Remote, United States Travel required: Approximately 30-40 days/year Salary: $68,000 annually ... Familiarity with program evaluation or data-informed instructional improvement. Competencies

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Showing results 21-40

Postdoc Data Science Remote information

See Philadelphia, PA salary details

$58K

$68.7K

$130.2K

How much do postdoc data science remote jobs pay per year?

As of Aug 30, 2026, the average yearly pay for postdoc data science remote in Philadelphia, PA is $68,657.00, according to ZipRecruiter salary data. Most workers in this role earn between $59,500.00 and $60,000.00 per year, depending on experience, location, and employer.

What is a postdoc data science remote?

A Postdoc Data Science Remote position is a postdoctoral research role focused on data science, where the work can be performed entirely or mostly from a remote location rather than on-site at a university or research institution. These positions typically involve advanced research in areas such as machine learning, statistics, or computational modeling, and are intended for individuals who have recently completed a PhD. Remote postdoc roles offer flexibility in work location while still providing opportunities to collaborate with academic or industry teams, publish research, and further develop specialized expertise in data science.

What are the key skills and qualifications needed to thrive as a postdoc data science remote?

To thrive as a Postdoc Data Science Remote, you need an advanced degree (typically a Ph.D.) in a quantitative field, strong statistical analysis skills, and proficiency in programming languages such as Python or R. Familiarity with machine learning frameworks, data visualization tools, and cloud computing platforms like AWS or Google Cloud is often required. Excellent problem-solving abilities, self-motivation, and effective communication skills are essential for independent research and collaboration in a remote environment. These competencies enable you to conduct high-level research, contribute valuable insights, and efficiently collaborate with global teams despite working remotely.

What are some typical challenges faced by remote postdoc data scientists when collaborating with research teams?

Remote Postdoc Data Scientists often encounter challenges related to communication and coordination across different time zones and digital platforms. Building rapport and maintaining effective collaboration with interdisciplinary teams can require extra effort, particularly when discussing complex research concepts or troubleshooting data issues. To overcome these hurdles, it’s important to proactively schedule regular virtual meetings, document workflows clearly, and leverage collaborative tools for code and data sharing. Developing strong digital communication skills and being adaptable to various team dynamics are essential for success in this role.

What is the difference between Postdoc Data Science Remote vs Data Scientist?

AspectPostdoc Data Science RemoteData Scientist
Required CredentialsPhD in Data Science, Statistics, or related fieldBachelor's or Master's in Data Science, Computer Science, or related field
Work EnvironmentRemote research-focused position, often academic or research institutionRemote or on-site, industry-focused, business or tech company
Employer & Industry UsageUniversities, research labs, academic institutionsTech companies, finance, healthcare, retail, industry
Common Search & ComparisonYesYes

The main difference is that a Postdoc Data Science Remote typically requires a PhD and focuses on research in academic or research settings, whereas a Data Scientist often holds a bachelor's or master's degree and works in industry, applying data analysis to business problems. Both roles may be remote, but their work environments and expectations differ significantly.

What are popular job titles related to Postdoc Data Science Remote jobs in Philadelphia, PA?

For Postdoc Data Science Remote jobs in Philadelphia, PA, the most frequently searched job titles are:

What job categories do people searching Postdoc Data Science Remote jobs in Philadelphia, PA look for?

The top searched job categories for Postdoc Data Science Remote jobs in Philadelphia, PA are:

Infographic showing various Postdoc Data Science Remote job openings in Philadelphia, PA as of July 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $68,657 per year, or $33 per hour.

Principal Data Scientist - Immunology - (2 positions)

Spring House, PA • On-site, Remote


Johnson & Johnson

8.3

Company rating: 8.3 out of 10

Based on 113 frontline employees who took The Breakroom Quiz

26th of 86 rated pharmaceutical

People enjoy working here

Good employer

Recommended by students


Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 13 days ago


Job description

At Johnson & Johnson,we believe health is everything. Our strength in healthcare innovation empowers us to build aworld where complex diseases are prevented, treated, and cured,where treatments are smarter and less invasive, andsolutions are personal.Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity.Learn more at jnj.com.

As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit.

Job Function:

Data Analytics & Computational Sciences

Job Sub Function:

Data Science

Job Category:

Scientific/Technology

All Job Posting Locations:

Cambridge, Massachusetts, United States of America, Raritan, New Jersey, United States of America, San Diego, California, United States of America, Spring House, Pennsylvania, United States of America, Titusville, New Jersey, United States of America

Job Description:

Our expertise in Innovative Medicine is informed and inspired by patients, whose insights fuel our science-based advancements. Visionaries like you work on teams that save lives by developing the medicines of tomorrow.

Join us in developing treatments, finding cures, and pioneering the path from lab to life while championing patients every step of the way.

Learn more athttps://www.jnj.com/innovative-medicine

Johnson & Johnson Innovative Medicine is currently seeking a Principal Data Scientist - Immunology (2 openings) to join our Immunology R&D Data Science & Digital Health team (DSDH). This position will be located on site at one of our offices in either Spring House PA, Cambridge MA, Titusville NJ, Raritan NJ, or San Diego CA (NO fully remote option available).

Johnson and Johnson Innovative Medicine is recruiting for aPrincipal Data Scientist (Knowledge Graph Engineer) - Immunology, who will play a pivotal role to standardize and connect biomedical and clinical data. You will be a hands-on technical contributor with depth in semantic technologies, ontology, and graph data modeling, plus strong familiarity with the life sciences domain.

You will connect enterprise master data with R&D data across the entire product lifecycle so trusted, interoperable knowledge powers analytics, search, and AI across Johnson and Johnson Innovative Medicine.

Primary Responsibilities:

  • Be a key contributor to the design and implementation of a scalable knowledge graph infrastructure focused on data standardization and interoperability, focusing on Immunology R&D data.
  • Apply graph-based data modeling for efficient Immunology R&D organization, integration and retrieval to ensure system flexibility and long-term maintainability.
  • Work with a larger community of Data Scientists, Clinical Scientists, and Discovery Scientists to standardize, curate and create AI-Ready data sets.
  • Curate and extend ontologies for clear mapping into established biomedical ontologies and controlled terminologies using resource description framework (RDF) standards.
  • Work with SPARQL/GraphQL/REST services; develop ingestion and curation pipelines to ingest, normalize and map concepts across data sources.
  • Extend and curate Immunology R&D-relevant ontologies (e.g., diseases, drugs, targets, pathways, etc.) and maintain synonyms, cross-references, and provenance.
  • Partner with cross-functional teams to enable NLP/RAG over graphs, features for predictive modeling and terminology services for search and study design tools.
  • Work with Data Science & Digital Health colleagues, IT and DevOps teams to deploy and manage the graph database infrastructure, focusing on high availability, scalability, and recovery operations specifically geared toward Immunology R&D needs and applications.
  • Draft and manage documentation, such as data dictionaries, data lineage, and data flow diagrams, to facilitate understanding of the knowledge graph.

Preferred Qualifications:

  • Desired Ph.D. or master's degree in bioengineering, computer science, IT, bioinformatics, physics, mathematics, or related fields, emphasis on semantic technologies for biomedical application.
  • 5+ years professional experience in health informatics.
  • Demonstrated experience in large-scale knowledge graphs construction, ontology development, pharmaceutical or healthcare domains integration.
  • Programming background in parser combinators, natural language processing, and linked data (RDF Triple Stores and property graphs).
  • Proficiency in semantic web technologies (e.g. SPARQL, RDF, OWL), familiarity with graph databases (Neo4j, Amazon Neptune).
  • Proven work with complex biomedical datasets (e.g. clinical, genomics, proteomics)
  • Proficiency in various data storage solutions (SQL, key-value, column, document, graph stores) and data modeling techniques (semantic data, ontologies, taxonomies).
  • Experience in CI/CD implementations, git usage, CI/CD stacks (Jenkins, GitLab, Azure DevOps), DevOps tools, metrics/monitoring, and containerization technologies (Docker, Singularity).
  • Demonstrated stakeholder management capabilities- including requirements gathering, business analysis and planning. Must have the capacity to translate discussions into user requirements and project plans.
  • Ability to manage a numerous projects simultaneously, prioritize work, exhibit organizational skills and flexibility to deliver maximum business value.
  • Willingness to conduct periodic travel (<15% of time) to conferences and internal meetings.

This position will be located on site at one of our campuses in either Spring House PA, Cambridge MA, Titusville NJ, Raritan NJ, or San Diego, CA (NO fully remote option available). Occasional travel for crossfunctional workshops, design sessions, and team meetings may be required.
Johnson & Johnson is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, protected veteran status or other characteristics protected by federal, state or local law. We actively seek qualified candidates who are protected veterans and individuals with disabilities as defined under VEVRAA and Section 503 of the Rehabilitation Act.
Johnson & Johnson is committed to providing an interview process that is inclusive of our applicants' needs. If you are an individual with a disability and would like to request an accommodation, external applicants please contact us via https://www.jnj.com/contact-us/careers , internal employees contact AskGS to be directed to your accommodation resource.
The anticipated base pay range for this position is $117,000 to $201,250. The Company maintains highly competitive, performance-based compensation programs. Under current guidelines, this position is eligible for an annual performance bonus in accordance with the terms of the applicable plan. The annual performance bonus is a cash bonus intended to provide an incentive to achieve annual targeted results by rewarding for individual and the corporation's performance over a calendar/performance year. Bonuses are awarded at the Company's discretion on an individual basis. Employees and/or eligible dependents may be eligible to participate in the following Company sponsored employee benefit programs: medical, dental, vision, life insurance, short- and long-term disability, business accident insurance, and group legal insurance. Employees may be eligible to participate in the Company's consolidated retirement plan (pension) and savings plan (401(k)).

Employees are eligible for the following time off benefits:
Vacation - up to 120 hours per calendar year
Sick time - up to 40 hours per calendar year
Holiday pay, including Floating Holidays - up to 13 days per calendar year of Work, Personal and Family Time - up to 40 hours per calendar year
Additional information can be found through the link below.https://www.careers.jnj.com/employee-benefits

The compensation and benefits information set forth in this posting applies to candidates hired in the United States. Candidates hired outside the United States will be eligible for compensation and benefits in accordance with their local market.


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Required Skills:

Preferred Skills:

Advanced Analytics, Coaching, Critical Thinking, Data Analysis, Data Privacy Standards, Data Quality, Data Reporting, Data Savvy, Data Science, Data Visualization, Digital Fluency, Econometric Models, Organizing, Process Improvements, Strategic Thinking, Technical Credibility, Workflow Analysis

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