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Postdoc Data Science Remote Jobs in Philadelphia, PA

Soni Resources

Data Scientist

Conshohocken, PA · On-site +1

$175K/yr

... Data Science + Data Engineering) Location: Remote (Preference for Northeast/Mid-Atlantic; monthly travel to Plymouth Meeting, PA as needed) Our client is building a data-driven culture where ...

Eastern University

Adjunct Faculty- Data Science

PA · On-site +1

Remote Optional Job Number: 515 Department: Data Science - (College of Health and Sciences) Opening Date: 01/25/2024 Join our vibrant community of dedicated faculty and staff who work to create a ...

Bread Financial

Lead Data Scientist

Chadds Ford, PA · On-site +1

$138K - $272K/yr

Bachelor's Degree in Statistics, Mathematics, Engineering, Data Science, Computer Science, or ... Normal office environment. (Remote or Hybrid), 3 to 4 days per month are required in office if ...

New

Campbell's

Data Scientist

Camden, NJ · On-site +1

$109K - $150K/yr

The Data Science Analyst plays a critical role in supporting the Demand Planning function by ... Hybrid work model based in Camden, NJ (Monday & Friday remote; Tuesday-Thursday in-office) * 10-15 ...

The Campbell?s Company

Data Scientist

Camden, NJ · On-site +1

$109K - $157K/yr

HOW YOU WILL MAKE HISTORY HERE The Data Science Analyst plays a critical role in supporting the ... Friday remote; Tuesday Thursday in-office)10 15% travel for company and customer ...

Pepperidge Farm, Incorporated

Data Scientist

Camden, NJ · On-site +1

$109K - $150K/yr

The Data Science Analyst plays a critical role in supporting the Demand Planning function by ... Hybrid work model based in Camden, NJ (Monday & Friday remote; Tuesday-Thursday in-office) * 10-15 ...

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All JobsPostdoc Data Science JobsPostdoc Data Science Remote JobsPostdoc Data Science Remote Jobs in Philadelphia, PA

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 Jul 19, 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 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 is a Postdoc Data Science Remote position?

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, and why are they important?

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 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:
Postdoc Data Science Remote jobs near you
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, 75% Full Time, 22% Part Time, and 2% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $68,657 per year, or $33 per hour.

VP of Data Science (Remote)

Forbes Advisor

Wilmington, DE • On-site, Remote

Full-time

Posted 13 days ago

Job description

At Forbes Advisor, our mission is to help readers turn their aspirations into reality. We arm people with trusted advice and guidance so they can make informed decisions they feel confident in and get back to doing the things they care about most.
We are an experienced team of industry experts dedicated to helping readers make smart decisions and choose the right products with ease. Forbes Advisor boasts decades of experience across dozens of geographies and teams, including Content, SEO, Business Intelligence, Finance, HR, Marketing, Production, Technology and Sales. The team brings rich industry knowledge to Forbes Advisor's global coverage of consumer credit, debt, health, home improvement, banking, investing, credit cards, small business, education, insurance, loans, real estate and travel.
Our Data & Analytics organisation builds the products, platforms and intelligence that power every marketing, product and commercial decision across the business. We're looking for a Data Science leader who believes machine learning only creates value when it changes business decisions.
This is an opportunity to build and lead a commercially driven Data Science function that delivers measurable improvements in customer acquisition, marketing performance and long-term business growth.
You'll lead a growing team of Data Scientists while partnering closely with Engineering, Analytics, Product and Commercial teams to ensure predictive models become trusted, production-ready products that drive measurable commercial outcomes. As we continue investing in first-party data, AI, machine learning and advanced marketing measurement, we're looking for an experienced Data Science leader to help shape the next phase of our commercial Data Science capability.
Responsibilties:
  • Commercial Data Science: Lead the strategy and delivery of predictive models that improve customer acquisition, marketing performance and long-term commercial value. You'll shape capabilities including lifetime value modelling, propensity modelling, customer segmentation, forecasting and value-based bidding, ensuring every model is linked to measurable business outcomes.
  • Marketing Science & Decision Science: Partner with Marketing, Product and Commercial teams to apply Data Science to real business problems. You'll help define how predictive analytics, experimentation and AI improve campaign performance, customer understanding and strategic decision making across platforms including Google and Meta.
  • Production Data Science: Work closely with Engineering and ML Ops to ensure models become reliable, production-ready products rather than one-off analyses. You'll champion reproducible experimentation, scalable deployment, model monitoring, retraining strategies and continuous improvement throughout the model lifecycle.
  • Leadership & Stakeholder Management: Lead and develop a growing team of Data Scientists while building trusted relationships across the business. You'll translate complex modelling into clear commercial recommendations, influence senior stakeholders through evidence, and help establish Data Science as a trusted driver of business strategy and commercial growth.
  • Innovation & Industry Leadership: Represent Forbes in strategic conversations with technology partners including Google and Meta while staying connected to advances in AI, machine learning and marketing science. You'll evaluate emerging technologies, bring new ideas into the organisation and help ensure our Data Science capability remains commercially relevant and technically leading.

Qualifications:
  • Experience leading commercial Data Science, Marketing Science or Decision Science teams.
  • Strong expertise in predictive analytics, customer analytics, machine learning and statistical modelling.
  • Experience applying Data Science to marketing performance, customer acquisition, lifetime value or value-based bidding.
  • Experience productionising machine learning solutions within modern cloud environments and working closely with Engineering and ML Ops teams.
  • Strong understanding of SQL, Python and modern machine learning frameworks.
  • Experience working with Google Ads, Meta or other major advertising platforms.
  • Excellent stakeholder management and communication skills, with the ability to influence both technical and commercial audiences.
  • Experience building and developing high-performing Data Science teams.
  • Strong commercial judgement, balancing technical excellence with measurable business impact.
  • A pragmatic approach to AI, applying emerging technologies where they create genuine commercial value.

Nice to Have
  • Experience within affiliate marketing, digital publishing or lead-generation businesses.
  • Experience working in financial services, insurance or regulated industries.
  • Experience working directly with Google or Meta Data Science teams.
  • Experience with attribution modelling and marketing measurement.
  • Experience building optimisation algorithms for DSPs or advertising platforms.
  • Experience with causal inference, experimentation frameworks or incrementality testing.
  • Experience forecasting marketing or commercial performance.
  • Experience with Vertex AI or equivalent cloud-based machine learning platforms.

Forbes Advisor provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.
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