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Fraud Detection Machine Learning Jobs in Norwalk, CT

Socure

Staff Data Scientist - Fraud & Risk

New York, NY · On-site

$180K - $210K/yr

... fraud detection. * Present findings and recommendations to technical and executive stakeholders with clarity and influence. * Stay current with advancements in AI and machine learning, applying ...

Fin

Risk Analyst

New York, NY · On-site

$100K - $175K/yr

Partner with the engineering team to design and implement fraud detection systems, leveraging machine learning and predictive analytics. * Ensure alignment with regulatory requirements, including AML ...

Fin

Risk Analyst

New York, NY · Remote

$100K - $175K/yr

Partner with the engineering team to design and implement fraud detection systems, leveraging machine learning and predictive analytics. * Ensure alignment with regulatory requirements, including AML ...

Fin

Risk Analyst

New York, NY · On-site +1

$100K - $175K/yr

Partner with the engineering team to design and implement fraud detection systems, leveraging machine learning and predictive analytics. * Ensure alignment with regulatory requirements, including AML ...

Varsity Tutors

Machine Learning Tutor

Mount Vernon, NY · Remote

$18 - $40/hr

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Varsity Tutors

Machine Learning Tutor

Bridgeport, CT · Remote

$18 - $40/hr

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Varsity Tutors

Machine Learning Tutor

New Rochelle, NY · Remote

$18 - $40/hr

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Varsity Tutors

Machine Learning Tutor

Stamford, CT · Remote

$18 - $40/hr

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Varsity Tutors

Machine Learning Tutor

Norwalk, CT · Remote

$18 - $40/hr

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Alloy

Senior Data Scientist

New York, NY · Hybrid

Our immediate focus is on fraud detection, where we believe machine learning can simplify and accelerate decision-making in ways traditional rule-based systems can't. Managing rules and policies to ...

Alloy

Senior Data Scientist

New York, NY · On-site

Our immediate focus is on fraud detection, where we believe machine learning can simplify and accelerate decision-making in ways traditional rule-based systems can't. Managing rules and policies to ...

Plaid Inc

Fraud and Abuse Operations Analyst

New York, NY · On-site

$138K - $163K/yr

Familiarity with machine learning models for fraud detection. * Fraud domain certifications (e.g., CFE/fraud examination background). * Exposure to production ML model lifecycles and metrics for ...

Warnerbros

Senior Machine Learning Engineer

New York, NY

$114K - $157K/yr

About the Role We're seeking a Senior Machine Learning Engineer to develop and deploy machine learning solutions for consumer growth, including fraud detection, pricing optimization, and user ...

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Fraud Detection Machine Learning information

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How much do fraud detection machine learning jobs pay per hour?

As of Jul 28, 2026, the average hourly pay for fraud detection machine learning in Norwalk, CT is $18.12, according to ZipRecruiter salary data. Most workers in this role earn between $14.95 and $19.33 per hour, depending on experience, location, and employer.

What are some common challenges faced by professionals working in Fraud Detection Machine Learning, and how can they be addressed?

Professionals in Fraud Detection Machine Learning often face challenges such as dealing with highly imbalanced datasets, rapidly evolving fraud patterns, and the need for real-time detection. Managing data imbalance requires careful selection of evaluation metrics and specialized algorithms. Staying ahead of new fraud tactics involves continuous model retraining and close collaboration with domain experts. Additionally, integrating machine learning solutions with existing systems often requires cross-functional teamwork with IT, security, and compliance teams.

What is fraud detection using machine learning?

Fraud detection using machine learning involves leveraging algorithms and data analysis techniques to identify suspicious or fraudulent activities in various domains, such as banking, e-commerce, or insurance. These systems analyze large volumes of transaction data to detect patterns or anomalies that may indicate fraud. Machine learning models can adapt over time, improving their accuracy as they are exposed to more data. This approach helps organizations automate and enhance their ability to prevent, detect, and respond to fraudulent behavior efficiently.

What is the difference between Fraud Detection Machine Learning vs Fraud Analyst?

AspectFraud Detection Machine LearningFraud Analyst
CredentialsData science, machine learning certifications, programming skillsFinance, criminal justice degrees, analytical skills
Work EnvironmentData-driven, tech-focused, often in financial or e-commerce sectorsInvestigative, report-focused, in financial institutions or insurance companies
Employer & IndustryTech companies, banks, e-commerce platformsFinancial institutions, insurance firms, retail

Fraud Detection Machine Learning involves developing algorithms to identify fraudulent activities automatically, relying heavily on data analysis and programming. Fraud Analysts manually investigate suspicious cases and interpret data insights. While both roles aim to prevent fraud, Machine Learning specialists focus on building models, whereas Fraud Analysts focus on case investigation and decision-making.

What are the key skills and qualifications needed to thrive as a Fraud Detection Machine Learning Specialist, and why are they important?

To thrive as a Fraud Detection Machine Learning Specialist, you need strong expertise in machine learning, statistical analysis, and programming languages like Python or R, typically supported by a degree in computer science, data science, or a related field. Familiarity with tools such as TensorFlow, Scikit-learn, SQL databases, and experience with big data platforms or cloud services is highly valuable. Critical thinking, attention to detail, and effective communication are crucial soft skills for identifying complex fraud patterns and collaborating with interdisciplinary teams. These competencies are vital for developing accurate models that protect organizations from financial losses and maintain trust with customers.
What are popular job titles related to Fraud Detection Machine Learning jobs in Norwalk, CT? For Fraud Detection Machine Learning jobs in Norwalk, CT, the most frequently searched job titles are:
What cities near Norwalk, CT are hiring for Fraud Detection Machine Learning jobs? Cities near Norwalk, CT with the most Fraud Detection Machine Learning job openings:
Fraud Detection Machine Learning jobs near you

Senior / Staff Machine Learning Engineer, Fraud

Radar Labs, Inc

New York, NY • On-site

$200K - $300K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 24 days ago

Job description

About Radar
Radar is the global leader in geolocation, with geofencing SDKs, maps APIs, and AI-enabled solutions for marketing, fraud, and operations teams.
Why is Radar the best place to work?
  • We're trusted by some of the world's best companies, from high-growth startups to the Fortune 500.
  • We have incredible scale: We're processing over 1 billion API calls per day from hundreds of millions of devices.
  • We're well-resourced, and we've raised $85.5M from world-class investors, including Accel and Insight Partners.
  • We have a high-performance culture, with ambitious and entrepreneurial teammates in every role.
  • We recently moved into an amazing new office in Flatiron, Manhattan, NYC.
  • We were recently named a top 10 best place to work in NYC by Crain's.

Despite our growth and scale, we're still just getting started. That's where you come in.
About the role
We're looking for Product Engineers to build machine learning-based anti-fraud systems into core Radar products. The ideal engineer for this role is someone who is primarily an ML engineer, and has built fraud detection models but wants to broaden their skills into other stacks like server or data. The perfect candidate will see themselves as a generalist who has built real ML systems and is ultimately motivated by driving impact to products and customers by building end-to-end features that leverage machine learning to prevent fraud.
How we work:
Most of our engineering team are former technical co-founders or former Radar interns from schools like Waterloo and CMU. Most engineers at Radar fit one of two molds, technically: either Staff level expertise in one stack, or "Multi-Stack" at any level. We say "Multi-Stack" because "Full-Stack" has the connotation of "Frontend and Backend", but Radar Engineers might also work on Mobile or Data engineering. Not that you need to be an expert in all of those, but a desire to learn, jump around to different stacks, and get things done is the important part.
We care a lot about shipping fast and talking to customers. We're committed to our product vision of full-stack location infrastructure, but we also know that customer feedback is a treasure map to gold. Even though Slack is the brain of our company, working together in-person in our NYC HQ is the fastest way for us to get things done. We meet on Mondays to plan out work for the week in small groups and use Linear for planning.
To us, a week is a long time, and we expect to ship big things every week.
The stack:
We have systems that leverage LightGBM and random forests using scikit and Rust and we need to build out new systems impacting additional products.
The server is a TypeScript Node.js app and a Geospatial Rust database we built called HorizonDB. We use MongoDB, S3/Athena, Redis, Airflow and everything is deployed to AWS.
Most engineers are in the on-call rotation.
How we use AI:
  • Engineers choose what AI tools they use, Claude and Codex being the most popular.
  • We're actively building Claude skills - for example we've taught it how to debug HorizonDB, our geospatial database.
  • All code changes are reviewed by an Engineer knowledgeable in that area. Claude and Codex also review all PRs.
  • There is a range of how much engineers use AI. Most use it daily if not weekly.
  • We are excited about what AI can do, but we also recognize the risks and don't compromise our coding standards.

The hiring process:
After a call with our Technical Recruiter, you'll do several technical Zoom calls with members of our engineering team: code screen, coding round, and system design round. If those go well we'll invite you to our NYC HQ for a final round interview. You'll meet one of our co-founders, someone from outside engineering, and meet more people from Radar. We'll go into more depth about how we work to see if there is a match.
What you'll do:
  • Work on core Radar ML infrastructure built with Python, Rust, Airflow, Spark and new systems you build
  • Build new systems for our Fraud products: anomaly detection, user and device risk scores, device fingerprinting, and emerging threat vectors
  • Work on features across several of backend, data infra and ML
  • Push the limits of fraud detection using many sensors on iOS and Android
  • Have your work run on 300M+ devices
  • Talk to Radar customers and prospects, hear their feedback, incorporate it into your work, and make them successful

You should:
  • Have experience building machine learning-based fraud detection products in production at scale
  • Are interested in talking to customers or prospects and making them successful
  • Are deeply curious about how things work, and have the tenacity to sit with hard problems and power through them

Bonus points if you:
  • Are a former technical co-founder
  • Have experience with anomaly detection, anti-fraud ML systems

You'll work with:
  • Nick Patrick, Co-Founder and CEO
  • Tim Julien, CTO
  • David Gurevich, Engineer
  • Our customers and prospects
  • Our Customer Success, Sales Engineering, and Sales teams

What we offer:
  • Competitive salary
  • Meaningful stock options in a fast-growing company
  • 401(k) plan with 4% match
  • New HQ in Flatiron, NYC
  • Top-notch equipment
  • Catered lunches
  • Unlimited PTO
  • Health, dental, and vision insurance with 100% coverage for employees
  • 12 weeks of paid parental leave
  • Commuter and fitness benefits

We'll share full details of our benefits package at the offer stage. Benefits may vary by location.
Radar is an equal opportunity employer and does not discriminate on the basis of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, veteran status, or any other characteristic protected by law.

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