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Data Scientist Machine Learning Jobs in Princeton, NJ

Data Scientist (Machine Learning)

New York, NY ยท On-site

$180K - $230K/yr

Move fast, learn fast: hundreds of experiments run monthly; rigorous experimentation culture Why this Role is Different Most Data Science roles currently on the market are focused on optimizing ad ...

Design and build data solutions using state-of-the-art machine learning and informatics methods ... Contribute to data science best practices and mentor team members to elevate the technical ...

We are looking for a Data Scientist to analyze large amounts of raw information to find patterns ... We also want to see a passion for machine-learning and research. Your goal will be to help our ...

We are looking for a Data Scientist to analyze large amounts of raw information to find patterns ... We also want to see a passion for machine-learning and research. Your goal will be to help our ...

Title and Summary Senior Data Scientist Overview: We are seeking a Senior Data Scientist to design ... Design, build, and deploy machine learning models for ad targeting, ranking, and bidding ...

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Data Scientist

New York, NY ยท On-site

$30 - $35/hr

Software Engineer / Data Scientist Full Time Atlanta, GA - Must be open to relocating anywhere in ... Exposure to machine learning frameworks such as scikit-learn, TensorFlow, or PyTorch. Experience ...

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Lead Data Scientist

New York, NY ยท Remote

$110K - $140K/yr

The role requires extensive experience in data analysis, agentic ai, statistical modeling, machine learning, and data visualization, as well as the ability to lead a team of data scientists and ...

The Senior Data Scientist will build machine learning-based tools and processes within the company's current big data infrastructure such as recommendation engines, automated propensity scoring ...

The Senior Data Scientist will build machine learning-based tools and processes within the company's current big data infrastructure such as recommendation engines, automated propensity scoring ...

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Showing results 1-20

Data Scientist Machine Learning information

See Princeton, NJ salary details

$39.3K

$128.7K

$206K

How much do data scientist machine learning jobs pay per year?

As of Aug 4, 2026, the average yearly pay for data scientist machine learning 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 scientist machine learning?

A Data Scientist specializing in Machine Learning (ML) uses statistical methods, algorithms, and computational power to analyze data and create predictive models. They work with large datasets to identify patterns, train machine learning models, and improve decision-making processes. Responsibilities often include data cleaning, feature engineering, model selection, and performance evaluation. They may collaborate with engineers and business teams to deploy models in real-world applications. Strong skills in programming (Python, R), ML frameworks (TensorFlow, Scikit-learn), and data visualization are essential.

What are the key skills and qualifications needed to thrive in the data scientist machine learning position, and why are they important?

To excel as a Data Scientist Machine Learning, you need a strong proficiency in statistics, programming (typically Python or R), and a solid understanding of machine learning algorithms, usually backed by a degree in computer science, mathematics, or a related field. Familiarity with tools such as TensorFlow, scikit-learn, SQL databases, and cloud platforms, as well as certifications in data science or machine learning, is commonly expected. Analytical thinking, problem-solving skills, and effective communication are vital soft skills in this profession. These qualifications combine to drive impactful insights and enable the successful development and deployment of machine learning models in business environments.

What are the typical day-to-day responsibilities of a data scientist machine learning?

On a typical day, a Data Scientist specializing in Machine Learning might gather and preprocess data, design and implement machine learning models, and evaluate their performance to solve real-world problems. They often collaborate with data engineers, software developers, and business stakeholders to translate business objectives into technical solutions and integrate models into existing systems. Other responsibilities can include visualizing data insights, conducting experiments to tune algorithms, and staying current with new developments in the field. The work is highly collaborative and iterative, requiring clear communication with various teams to ensure project goals are met efficiently.

What are popular job titles related to Data Scientist Machine Learning jobs in Princeton, NJ? For Data Scientist Machine Learning jobs in Princeton, NJ, the most frequently searched job titles are:
What job categories do people searching Data Scientist Machine Learning jobs in Princeton, NJ look for? The top searched job categories for Data Scientist Machine Learning jobs in Princeton, NJ are:
What cities near Princeton, NJ are hiring for Data Scientist Machine Learning jobs? Cities near Princeton, NJ with the most Data Scientist Machine Learning job openings:
Infographic showing various Data Scientist Machine Learning job openings in Princeton, NJ as of July 2026, with employment types broken down into 1% As Needed, 81% Full Time, 13% Part Time, 1% Temporary, and 4% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $128,663 per year, or $61.9 per hour.

Data Scientist (Machine Learning)

Nelo Mobile

New York, NY โ€ข On-site

$180K - $230K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 15 days ago


Job description

About Nelo
Nelo is a leading fintech in Mexico reimagining credit to expand consumer buying power. Founded in 2019 by former Uber international growth team leads Kyle Miller and Stephen Hebson, Nelo offers credit cards, BNPL loans, bill payments, and its own marketplace - all under one app - designed from first principles for a mobile-first, real-time payments world.
With $100M in annual revenue, $1B in annualized GMV, and $140M+ raised in equity and debt, Nelo is one of the most capital-efficient consumer fintech companies in Latin America. The company is profitable - positive operating profit in both 2024 and 2025. It runs lean and technical: 60 employees, 8 engineers, with AI driving underwriting, collections, and operations.
  • HQ: Mexico City, Mexico; commercial and people operations in New York City
  • Founded: 2019
  • Team size: 60 FTEs
  • Open roles: 10+
  • Website: nelo.mx
  • Stage: Post-Series A; $100M credit facility (Victory Park Capital, 2022); profitable
  • Benefits: 401k, open PTO, medical, dental, vision, STD, LTD, fertility

Company values:
  • Be your best selves: ambition, hard work, intellectual curiosity
  • Everyone is an owner: all employees receive equity including customer support; 10-year option expiration; equity refreshers
  • Customer first: product decisions grounded in customer benefit
  • Open and honest communication: quarterly financials and board presentations shared company-wide; low tolerance for bureaucracy or gossip
  • Move fast, learn fast: hundreds of experiments run monthly; rigorous experimentation culture
Why this Role is Different
Most Data Science roles currently on the market are focused on optimizing ad clicks or slightly improving recommendation engines.
This isn't that.
At Nelo, your models are the product. You are building the decision engine that determines who gets access to credit in an emerging market. This involves high-stakes constrained optimization problems where "good enough" mathematics will result in direct financial loss.
We are looking for the type of person who is frustrated by the "black box" approach of modern libraries and actually understands the statistical theory and causality behind the code. If you want to apply academic-level rigor to a P&L that is scaling rapidly, this is your seat.
What You'll Do:
  • Solve the "Why," not just the "What": You will design and deploy causal inference models to drive our underwriting and portfolio management strategies. Correlation isn't enough when you're managing risk.
  • Build the Core Engine: You will create and refine the algorithms for credit pricing, personalization, and ranking. Your code will directly impact the wallet of the consumer and the margin of the company.
  • Own the Infrastructure: You won't just hand off a Jupyter notebook to an engineer. You will lead ML infrastructure projects, ensuring observability and operational excellence for the models you build.
Who You Are:
  • You have deep theoretical roots. We are explicitly looking for candidates with a strong academic background (PhD preferred) who understand the first principles of classification, forecasting, and optimization.
  • You are a builder, not just a researcher. While you love the theory, you have at least 5 years of experience applying it in a production environment. You write production-grade Python and SQL.
  • You value velocity. You understand that a perfect model shipped next year is worth less than a great model shipped next week. You can balance intellectual rigor with the need to execute.
  • You are happy in NYC. This is an in-office role. We believe the hardest problems are solved when smart people are in the same room with a whiteboard.
What's on the Table
  • Significant Equity (You're building the company, you should own it).
  • 100% medical, dental & vision insurance coverage for you (50% for dependents).
  • Unlimited PTO (that we actually expect you to take).
  • 401(k).
  • Extended maternity and paternity leave.
  • Relocation support and Sabbatical program.
About the Process
We know you're busy, so we don't do 8-stage interviews.
  1. Quick chat with the Hiring Manager to align on expectations.
  2. A business case/technical assessment (relevant to the actual job).
  3. Onsite interview in NYC to meet the team.
  4. Offer.
This isn't a job for someone who wants to hide in the back office; it's for someone who wants their math to move the market.