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Scientific Machine Learning Jobs in Red Bank, NJ

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 ...

Capital One

Lead Machine Learning Engineer

New York, NY · On-site +1

$112K - $147K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar ...

Arlo

Machine Learning Engineer

New York, NY · On-site

$180K - $230K/yr

Arlo's underwriting is the core of the business, and it runs on machine learning at serious scale ... You'll also build the tooling that lets our data scientists and actuaries iterate faster than ever.

Crowe LLP

Machine Learning Intern

New York, NY · On-site

$27 - $42/hr

Role Summary The data science (DS) internship at Crowe follows the firmwide calendar, approximately overlapping the academic summer. DS interns will have a designated data scientist mentor and will ...

Arlo

Machine Learning Engineer

New York, NY · On-site

$180K - $230K/yr

Arlo's underwriting is the core of the business, and it runs on machine learning at serious scale ... You'll also build the tooling that lets our data scientists and actuaries iterate faster than ever.

Crowe LLP

Machine Learning Intern

New York, NY

$27 - $42/hr

Role Summary The data science (DS) internship at Crowe follows the firmwide calendar, approximately overlapping the academic summer. DS interns will have a designated data scientist mentor and will ...

Teleskope

Machine Learning Engineer

New York, NY · On-site

$160K - $210K/yr

About the role We are seeking a Machine Learning Engineer to strengthen our element classification system - working closely with data scientists and data annotators to ship and improve entity ...

Capital One

Lead Machine Learning Engineer

New York, NY · On-site +1

$112K - $147K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar ...

Zencastr

Senior Machine Learning Engineer (Remote)

New York, NY · On-site +1

$114K - $157K/yr

We are looking for an outstanding machine learning engineer to join our team! The role will provide ... As an integral part of the squad, you will collaborate with research scientists, data scientists ...

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All JobsScientific Machine Learning JobsScientific Machine Learning Jobs in Red Bank, NJ

Scientific Machine Learning information

See Red Bank, NJ salary details

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How much do scientific machine learning jobs pay per hour?

As of Aug 20, 2026, the average hourly pay for scientific machine learning in Red Bank, NJ is $32.30, according to ZipRecruiter salary data. Most workers in this role earn between $19.71 and $41.20 per hour, depending on experience, location, and employer.

What is scientific machine learning?

Scientific machine learning (SciML) is an interdisciplinary field that combines principles from machine learning and scientific computing to solve complex scientific and engineering problems. It involves developing algorithms and models that can learn from data and physical laws, such as differential equations, to make predictions, optimize systems, or gain insights into phenomena. SciML is widely used in areas like physics, biology, climate science, and engineering, enabling researchers to accelerate simulations and make data-driven discoveries. The field often leverages both traditional numerical methods and modern machine learning techniques, making it a rapidly evolving area of research.

What are the key skills and qualifications needed to thrive as a scientific machine learning professional, and why are they important?

To thrive as a Scientific Machine Learning professional, you need a strong background in mathematics, statistics, programming (often Python), and domain-specific scientific knowledge, typically with a graduate degree in a STEM field. Proficiency in machine learning frameworks (such as TensorFlow or PyTorch), scientific computing tools (like NumPy, SciPy), and experience with high-performance computing are commonly required. Critical thinking, problem-solving, and collaborative communication are vital soft skills for designing experiments and interpreting complex data. These skills ensure robust, reproducible results and the ability to bridge scientific inquiry with advanced computational methods.

What are some common challenges faced by professionals in scientific machine learning, and how can they be addressed?

Professionals in Scientific Machine Learning often encounter challenges such as integrating domain-specific scientific knowledge with machine learning models, managing large and complex datasets, and ensuring that models are interpretable and physically consistent. Collaboration with domain experts and interdisciplinary teams is essential to bridge knowledge gaps and validate results. To address these challenges, it is helpful to invest time in understanding the underlying scientific principles, keep up-to-date with advancements in both machine learning and scientific fields, and utilize specialized tools and frameworks designed for scientific data.

What is the difference between Scientific Machine Learning vs Data Scientist?

AspectScientific Machine LearningData Scientist
Required credentialsAdvanced degrees in CS, ML, or related fields; knowledge of scientific computingDegree in CS, statistics, or related fields; strong analytical skills
Work environmentResearch labs, academia, industry R&D teamsBusiness analytics, tech companies, consulting firms
Industry usageResearch, scientific computing, engineering simulationsBusiness insights, predictive modeling, data analysis

Scientific Machine Learning focuses on integrating scientific knowledge with machine learning techniques for research and engineering applications. Data Scientists analyze data to extract insights and build predictive models for business or operational purposes. While both roles require strong technical skills, Scientific Machine Learning emphasizes scientific computing and domain-specific modeling, whereas Data Scientists focus on data analysis and visualization.

What cities near Red Bank, NJ are hiring for Scientific Machine Learning jobs?

Cities near Red Bank, NJ with the most Scientific Machine Learning job openings:

Scientific Machine Learning jobs near you
Infographic showing various Scientific Machine Learning job openings in Red Bank, NJ as of August 2026, with employment types broken down into 1% As Needed, 70% Full Time, 25% Part Time, 2% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $67,190 per year, or $32.3 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 yesterday

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