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Temporary Google Data Science Jobs in Warren, NJ

Artefact

Director, AI & Data Science

Manhattan, NY · On-site

... data scientists, data engineers, and digital experts are all dedicated to bringing extra value to ... Architecting and deploying solutions on Google Gemini Enterprise and Vertex AI as the primary stack ...

Artefact

Director, AI & Data Science

Manhattan, NY

... data scientists, data engineers, and digital experts are all dedicated to bringing extra value to ... Architecting and deploying solutions on Google Gemini Enterprise and Vertex AI as the primary stack ...

Publicis Groupe Holdings B.V

Data Scientist

Manhattan, NY · On-site

$72K - $109K/yr

... Data Science practice. Qualifications We're looking for relevant academic, research or work ... Temporary roles may be eligible to participate in our freelancer/temporary employee medical plan ...

Publicis Groupe Holdings B.V

Data Scientist

Manhattan, NY · On-site

$72K - $109K/yr

... Data Science practice. Qualifications We're looking for relevant academic, research or work ... Temporary roles may be eligible to participate in our freelancer/temporary employee medical plan ...

TekShapers

Senior Data Scientist

Raritan, NJ · On-site

Proficiency with Google Cloud Platform (Google Cloud Platform) and its AI/ML offerings (e.g ... Higher education (e.g., Master's degree in Computer Science, Information Technology, Data Science ...

Judge Group, Inc.

Data Scientist IV

Bridgewater, NJ · On-site

Experience with cloud platforms (Google Cloud Platform) and data warehousing solutions. Qualifications: Bachelor's or Master's degree in Data Science, Statistics, Economics, Business Administration ...

Clay Labs

Data Science & Analytics Manager

New York, NY · On-site

$240K - $300K/yr

We're already helping thousands of customers - including Anthropic, Notion, Google, and Ramp - go ... DSA is a team of data scientists and analytics engineers that serves as the company's center of ...

Posted today

Judge Group, Inc.

Data Scientist IV

Bridgewater, NJ · On-site

Experience with cloud platforms (Google Cloud Platform) and data warehousing solutions. Qualifications: Bachelor's or Master's degree in Data Science, Statistics, Economics, Business Administration ...

Wise Equation Solutions Inc.

Data Scientist

Newark, NJ · On-site

Proficiency in Python and/or R for data science and ML development * Experience building and ... Experience with cloud platforms -- AWS, Azure, or Google Cloud Platform * Familiarity with MLflow ...

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Temporary Google Data Science information

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$38.9K

$127.5K

$204.1K

How much do temporary google data science jobs pay per year?

As of Aug 21, 2026, the average yearly pay for temporary google data science in Warren, NJ is $127,464.00, according to ZipRecruiter salary data. Most workers in this role earn between $102,300.00 and $141,200.00 per year, depending on experience, location, and employer.

What is a temporary Google data scientist?

Temporary Google data science jobs are short-term positions at Google where professionals work on data-driven projects, such as analyzing large datasets, building predictive models, and providing actionable insights. These roles often last from a few months up to a year and can be part of contract work, internships, or project-based assignments. Temporary data scientists at Google collaborate with teams across the company to solve complex problems, improve products, and support decision-making. These positions usually require strong analytical skills, experience with programming languages like Python or R, and familiarity with machine learning techniques.

What are some typical challenges faced by data scientists in temporary roles at Google?

Temporary data scientists at Google often face the challenge of quickly onboarding to new projects and adapting to the company's fast-paced environment. Since assignments are time-bound, there’s a need to rapidly understand existing data infrastructure, collaborate with diverse teams, and deliver actionable insights within tight deadlines. Additionally, building rapport with permanent staff and accessing proprietary data or tools can require extra initiative. However, these challenges provide valuable exposure to Google’s cutting-edge practices and can significantly enhance your professional network and skill set.

What are the key skills and qualifications needed to thrive as a temporary Google data scientist, and why are they important?

To thrive as a Temporary Google Data Scientist, you need strong analytical skills, expertise in statistics, and a solid foundation in programming languages such as Python or R, typically supported by a degree in a quantitative field. Familiarity with machine learning frameworks, big data tools like SQL and TensorFlow, and experience with data visualization platforms such as Tableau are highly valuable. Strong problem-solving abilities, adaptability, and effective communication skills are crucial for collaborating on fast-paced projects and presenting findings to diverse stakeholders. These competencies enable data-driven decision-making and ensure impactful contributions within a dynamic, innovative environment.
Temporary Google Data Science jobs near you

Research Scientist, Foundational Data Science

Prior Labs

New York, NY • On-site

Full-time

Re-posted 20 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.
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