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Data Science New Grad Jobs in Princeton, NJ (NOW HIRING)

Omnicom

Associate Director, Data Science

New York, NY · On-site

$64K - $65K/yr

Data Science and AI PHD is a global communications planning and media buying agency network ... Finding a better way is our ethos and sums up how we approach everything - from a new client brief ...

Omnicom

Associate Director, Data Science

New York, NY · Hybrid

$64K - $65K/yr

Data Science and AI PHD is a global communications planning and media buying agency network ... Finding a better way is our ethos and sums up how we approach everything - from a new client brief ...

Jj

Principal Scientist, Data Science

New Brunswick, NJ · On-site +1

$169K - $171K/yr

New Brunswick, NJ Job Type: Full-Time Rate of Pay: $169,541 - $171,000/year Job Duties: Closely partner with R&D Data Science and Digital Health, as well as multidisciplinary teams within J&J ...

Meta

Data Science Director

New York, NY · On-site

$314K/yr

You will use data to shape development, quantify new opportunities, identify upcoming challenges ... Data Science Director Responsibilities: * Inspire, lead and grow a distributed team of data ...

Noom US

Agentic Engineer (New Grad)

Princeton, NJ · On-site

$75K - $85K/yr

About the Role As we continue to grow, we're seeking an Agentic Engineer (New Grad) to help build ... Collaborate cross-functionally with engineering, data science, and product teams * Stay current ...

Noom US

Agentic Engineer (New Grad)

Princeton, NJ · On-site

$75K - $85K/yr

About the Role As we continue to grow, we're seeking an Agentic Engineer (New Grad) to help build ... Collaborate cross-functionally with engineering, data science, and product teams * Stay current ...

Medidata Solutions

Lead Data Science Engineer

New York, NY · On-site

$135K - $180K/yr

New York, Hybrid Medidata follows a hybrid office policy in which employees who are hired for an in ... Apply advanced skills in data architecture, data science engineering, data modeling, and data ...

3ds

Lead Data Science Engineer

New York, NY · On-site

$135K - $180K/yr

New York, Hybrid Medidata follows a hybrid office policy in which employees who are hired for an in ... Apply advanced skills in data architecture, data science engineering, data modeling, and data ...

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Showing results 41-60

All JobsData Science New Grad JobsData Science New Grad Jobs in Princeton, NJ

Data Science New Grad information

See Princeton, NJ salary details

$39.3K

$128.7K

$206K

How much do data science new grad jobs pay per year?

As of Sep 7, 2026, the average yearly pay for data science new grad in Princeton, NJ is $128,663.00, according to ZipRecruiter salary data. Most workers in this role earn between $103,300.00 and $142,600.00 per year, depending on experience, location, and employer.

What is a data science new grad?

Data Science New Grad roles are entry-level positions designed for recent graduates who have completed a degree in data science, computer science, statistics, or a related field. These roles typically involve working with data to analyze trends, build predictive models, and support business decision-making. New grads are expected to have foundational knowledge in programming, statistics, and machine learning, but are not required to have extensive work experience. These roles often offer mentorship and training to help new professionals grow their technical and analytical skills. Companies hire Data Science New Grads to bring fresh perspectives and to develop future data science talent.

What are the key skills and qualifications needed to thrive as a data science new grad?

To thrive as a Data Science New Grad, you need a strong foundation in statistics, programming (typically Python or R), and data analysis, often supported by a degree in computer science, mathematics, or a related field. Familiarity with machine learning frameworks (such as TensorFlow or scikit-learn), data visualization tools, and SQL databases is highly valued. Strong problem-solving abilities, communication skills, and curiosity help new grads stand out when interpreting data and presenting insights. These competencies are crucial for transforming complex data into actionable business solutions and collaborating effectively within multidisciplinary teams.

What types of projects can a data science new grad expect to work on during their first year?

As a Data Science New Grad, you can expect to work on a variety of projects such as cleaning and preprocessing data, developing predictive models, and assisting with data visualization and reporting. You may also collaborate closely with product managers, engineers, and senior data scientists to translate business problems into analytical solutions. Early projects often focus on building foundational skills and understanding the company’s data infrastructure, while gradually increasing in complexity as you gain experience. This hands-on exposure is designed to help you grow technically and understand how data science supports organizational goals.

What are popular job titles related to Data Science New Grad jobs in Princeton, NJ?

For Data Science New Grad jobs in Princeton, NJ, the most frequently searched job titles are:

What job categories do people searching Data Science New Grad jobs in Princeton, NJ look for?

The top searched job categories for Data Science New Grad jobs in Princeton, NJ are:

What cities near Princeton, NJ are hiring for Data Science New Grad jobs?

Cities near Princeton, NJ with the most Data Science New Grad job openings:

Data Science New Grad jobs near you
Infographic showing various Data Science New Grad job openings in Princeton, NJ as of August 2026, with employment types broken down into 33% Internship, 34% Full Time, and 33% Part Time. Highlights an 33% In-person, and 67% Remote job distribution, with an average salary of $128,663 per year, or $61.9 per hour.

Research Scientist, Foundational Data Science

Prior Labs

New York, NY • On-site

Full-time

Re-posted 7 days ago

Job description

Who we are
Foundation models transformed text and images. Structured data - the largest and most consequential data format in the world - stayed untouched, until now. What LLMs did for language, we're doing for tables.
We pioneered tabular foundation models: TabPFN v2 was a Nature cover story, has passed 3.5M+ downloads and 7,500+ GitHub stars, and runs in production from detecting lung disease with Oxford Cancer Analytics to preventing train failures with Hitachi. The hardest problems - millions of rows, real-time inference, entirely new modalities - are still open, and no one else is working on them at this level.
We're a small, highly selective team of 40+ with backgrounds from Google, DeepMind, Meta, Apple, Amazon, Jane Street, and CERN, led by Frank Hutter, Noah Hollmann, and Sauraj Gambhir, and advised by Bernhard Schölkopf and Turing Award winner Yann LeCun.
In July 2026, less than 18 months after our €9M pre-seed, we joined SAP as an independent frontier AI lab - same team, mission, and open-weights models, now backed by more than €1 billion over four years.
What you'll do
This role is foundational data science: building the foundations of tabular foundation models so a single model can solve data-science problems across the board. Roughly half the work is inventing new frontier tools for TFMs, and half is building the dataset and benchmark bedrock they stand on.
  • Invent and build the frontier tools that extend TabPFN, including its thinking, scaling, and agentic capabilities, and the new methods that let one model generalize across the full landscape of data-science problems. This is the most open-ended part of the work and grows over time.
  • Set the research direction by deciding which model capabilities and benchmarks are worth pursuing, choosing what is worth solving rather than optimizing a score someone else set.
  • Bring in external research and real customer needs to shape new model and tooling directions, and publish frontier results that move the field forward.
  • Build trustworthy benchmarks from the structured data behind real, high-impact problems, so the team optimizes for real-world performance rather than one leaderboard.
  • Faithfully implement the baselines and competitor models that set the gold standard of applied data science, giving the team a read on where TabPFN leads and where there is room to improve.
  • Build an automated, agentic pipeline with a human in the loop so this data and benchmark foundation scales to far larger volumes without losing rigor, itself a genuinely new tool.

What we're looking for
  • You have solved data-science problems across many domains and datasets to a high standard, optimizing for strong performance across a whole suite of tasks rather than the single best score on one.
  • You work undogmatically across the ML toolbox, including getting strong results with gradient-boosted trees (such as XGBoost) and not only with deep learning.
  • You understand the common categories of dataset defects (leakage, label noise, distribution shift, duplication, mislabeled targets, and similar) and why each corrupts a training or benchmark signal.
  • You are energized by foundational work, valuing the dataset and benchmark bedrock as much as the frontier tooling, and you have taken on hard problems others passed over.
  • You thrive as a senior individual contributor in an ambiguous, early-stage, low-process environment. You are opinionated on best practice in Data Science and can make good judgement calls on approaches to complex problems.

Nice to have
  • Experience building or extending evaluation harnesses, benchmark suites, or experiment frameworks that others rely on.
  • Experience building LLM- or agent-assisted pipelines with a human in the loop to scale a previously manual workflow.
  • Experience acting as the link between external research or customer needs and an internal model or product roadmap.
  • Prior work on tabular, structured-data, or foundation-model problems, or helping shape an emerging research subfield through community work.

Life at Prior Labs
You'll work alongside researchers and builders who hold themselves to a very high bar - in the quality of their work and in how they work with each other. We move fast and still take the time to do things right.
Our teams are based in Berlin, Freiburg, and New York - when you're working on something as hard as TabPFN, being in the same room matters. But great people come from everywhere, and in exceptional cases we're open to remote, which usually means frequent travel to one of our offices. Wherever you're based, the whole company comes together regularly for offsites to build and celebrate together.
Our Commitments
The best products and teams are built by people with a wide range of perspectives and backgrounds. We welcome applications from all identities and walks of life - especially if you've ever felt discouraged by "not checking every box" - and provide equal opportunities regardless of gender, sexual orientation, origin, disability, or any other trait that makes you who you are.
We care about how your data is handled - see our Recruiting Data Privacy page

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