ZipRecruiter

Log In

1

Data Scientist Machine Learning Jobs in New York

Nelo Mobile

Data Scientist (Machine Learning)

New York, NY · 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 ...

Nestle

Senior Data Scientist

Bridgewater, NJ · On-site

Analyze large and complex datasets to identify patterns, build statistical and machine learning ... Integrate the latest data science innovations into product solutions, enhancing data, analytical ...

NYULMC

Data Scientist & Engineer

New York, NY · On-site

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 ...

Forhyre

Data Scientist

New York, NY

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 ...

BMW Group

Lead Data Scientist

Woodcliff Lake, NJ · On-site

$181K - $201K/yr

Lead Data Scientist Posting Start Date: 7/20/26 Job Location (Long): Woodcliff Lake, New Jersey ... machine learning methods, and recommend improvements; work with large data sets from inside and ...

Forhyre

Data Scientist

New York, NY

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 ...

next page

Showing results 1-20

All JobsData Scientist Machine Learning JobsData Scientist Machine Learning Jobs in New York

Data Scientist Machine Learning information

See New York salary details

$41K

$134.3K

$215K

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

As of Jul 30, 2026, the average yearly pay for data scientist machine learning in New York is $134,280.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,800.00 and $148,800.00 per year, depending on experience, location, and employer.

What is a Data Scientist Machine Learning job?

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.

Is 40 too late for data science?

Data scientists can enter the field at any age, including 40 or older, as success depends on skills, experience, and continuous learning. Many professionals transition into data science later in their careers by acquiring relevant knowledge in programming, statistics, and machine learning tools. Age is less important than demonstrated expertise and the ability to adapt to evolving technologies.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and deploy AI models, and while AI automation tools can assist with certain tasks, MLEs are essential for creating and maintaining complex systems. AI is a tool that enhances their work but does not replace the need for skilled professionals who understand data, algorithms, and system integration.

Which 5 jobs will survive AI?

Data Scientist Machine Learning roles are likely to persist as they require complex problem-solving, domain expertise, and the ability to interpret and communicate insights from data. Jobs that involve creativity, emotional intelligence, and strategic decision-making, such as healthcare professionals, educators, and skilled trades, are also expected to remain resilient despite AI advancements.

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.

Do data scientists do machine learning?

Yes, data scientists often use machine learning techniques to analyze data, build predictive models, and extract insights. Proficiency in programming languages like Python or R and understanding of algorithms are essential skills for applying machine learning in their work.
What are the most commonly searched types of Data Scientist Machine Learning jobs in New York? The most popular types of Data Scientist Machine Learning jobs in New York are:
What are popular job titles related to Data Scientist Machine Learning jobs in New York? For Data Scientist Machine Learning jobs in New York, the most frequently searched job titles are:
What job categories do people searching Data Scientist Machine Learning jobs in New York look for? The top searched job categories for Data Scientist Machine Learning jobs in New York are:
Data Scientist Machine Learning jobs near you
Infographic showing various Data Scientist Machine Learning job openings in New York 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 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $134,280 per year, or $64.6 per hour.

Data Scientist (Machine Learning)

Nelo Mobile

New York, NY • On-site

$180K - $230K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 10 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.

Apply