Job description

Alloy is where you belong! Alloy is the AI-powered identity and fraud prevention platform that accelerates onboarding, stops fraud, and scales compliance across the customer lifecycle so financial organizations can grow without limits. More than 900 of the world's leading financial institutions and fintechs trust Alloy for smarter risk management that drives growth. Through our values: Be Bold, Go Fast, Collaborate, and Celebrate Our Differences, we are creating a workplace where you can grow, thrive, and belong. See how we’ve been continuously recognized and named one of Inc. Magazine’s Best Workplaces , Forbes America’s Best Startup Employers , Best Fintech to Work for by American Banker , year after year. Check out our investors and read more about us here . About the team The Signals team builds Alloy’s real-time machine learning systems at scale. 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 detect fraud is complex and constantly evolving; we use ML to make it smarter, faster, and more adaptive. Our approach is identity-centric, combining signals from a wide range of data sources to build a comprehensive understanding of risk. You will work on advancing our core models while also partnering directly with customers to drive strong outcomes from fraud studies. Alloy operates in a hybrid work environment. We look to foster collaboration and community by having our local employees onsite three days a week. What you'll be doing Contribute to the design, training, and evaluation of machine learning models that power Alloy’s fraud detection capabilities. Develop testing plans, metrics, performance reports, and translate findings into actionable recommendations. Support production ML workflows, including feature generation, model training, and monitoring, to ensure models remain accurate and reliable at scale. Document findings and communicate insights to internal teams, contributing to shared learning and continuous improvement. Maintain up-to-date model documentation and support Alloy’s model governance processes to ensure transparency and compliance. Stay current with industry trends in applied ML and fraud detection, and contribute to Alloy’s mission of making financial services safer and more accessible. Who we’re looking for Always building with end-solution in mind. Able to communicate complicated concepts to a non-technical audience without diluting the complexity of the work. Able to build strong cross-functional relationships within Alloy. Naturally curious with a knack for asking tough questions. Solid understanding of core ML concepts such as supervised learning, feature engineering, and model evaluation. A team player. You believe that big things happen when the right people are working together. A fast learner Humble. Mistakes happen and owning them helps us learn and move on quickly You have: 8+ years as an individual contributor in Applied Fraud Research, Data Science, or Machine Learning with a proven track record in a “Solutions” or client-facing capacity. Expertise in working with highly imbalanced datasets and building production-grade Machine Learning models with specific interest in tree-based models. Advanced proficiency in scripting languages like Python and querying languages like SQL Proven ability to wrangle and think thoughtfully about data at scale (processing billions of records). Experience developing metrics and dashboards. Able to communicate their findings effectively to technical and nontechnical members Someone who embodies our shared Alloy values: be bold, get scrappy, collaborate, and celebrate our differences. You have experience in a highly analytical role in fast-paced environments Must be local to Greater New York City. Nice to Haves: Previous experience in financial fraud detection. Advanced Degree (Masters or PhD) in a quantitative field. Experience managing the end-to-end lifecycle of a technical pilot or Proof of Concept. Experience with BI tools like Looker. Experience with modeling on graph structures. We're a lean team, so your impact will be felt immediately, and opportunities will grow as the company scales up. If this all sounds like a good fit for you, why not join us? Alloy is committed to fair and equitable compensation practices. Below is the anticipated starting base compensation range for this role; however, pay may vary depending on job-related knowledge, in-demand skills, relevant experience, and/or geography. In addition to a competitive base salary, this position is also eligible for equity awards in the form of stock options (ISOs) as well as a competitive total benefits package. Your recruiter will be happy to walk you through the details and what compensation could look like for you specifically! This position has a salary range of $159,000, to $230,000. Benefits and Perks Unlimited PTO and flexible work policy Employee stock options Medical, dental, vision plans with HSA (monthly employer contribution) and FSA options 401k with 100% match up to 4% of annual employee compensation Eligible new parents receive 16 weeks of paid parental leave Home office stipend for new employees Annual Learning & Development annual stipend Well-being benefits include access to ClassPass, OneMedical, UrbanSitter, and Spring Health Hybrid work environment: employees are expected to work Tuesdays through Thursdays from our HQ in Union Square, Manhattan. Tasty lunches catered from a variety of local restaurants and frequent employee-organized cultural events contribute to our positive office energy. On Monday/Friday most employees Zoom into work from home while some take advantage of the quieter office. How to apply Apply right here! You've found the application! Alloy is proud to be an equal-opportunity workplace and employer. We’re committed to equal opportunity regardless of race, color, ancestry, religion, gender, gender identity, parental or pregnancy status, national origin, sexual orientation, age, citizenship, marital status, disability, or veteran status. We are committed to an inclusive interview experience and provide reasonable accommodations to applicants with visible and invisible disabilities. We encourage applicants to share needed accommodations with their recruiter. All Alloy jobs are listed on our careers page. Any communication during the recruitment process, including interview requests or job offers, will come directly from a recruiting team member with an alloy.com email address. We do not use outside applications or automated text messaging in our recruiting process. We will not ask for any sensitive financial or identification information during the recruiting process. If you’re ever unsure, please contact us directly via our website before sharing personal information.

Requirements

Must-haves

Alloy is where you belong!
About the team
You will work on advancing our core models while also partnering directly with customers to drive strong outcomes from fraud studies.
Alloy operates in a hybrid work environment. We look to foster collaboration and community by having our local employees onsite three days a week.
What you'll be doing
Contribute to the design, training, and evaluation of machine learning models that power Alloy’s fraud detection capabilities.
Develop testing plans, metrics, performance reports, and translate findings into actionable recommendations.
Support production ML workflows, including feature generation, model training, and monitoring, to ensure models remain accurate and reliable at scale.
Document findings and communicate insights to internal teams, contributing to shared learning and continuous improvement.
Maintain up-to-date model documentation and support Alloy’s model governance processes to ensure transparency and compliance.
Stay current with industry trends in applied ML and fraud detection, and contribute to Alloy’s mission of making financial services safer and more accessible.
Who we’re looking for
Always building with end-solution in mind.
Able to communicate complicated concepts to a non-technical audience without diluting the complexity of the work.
Able to build strong cross-functional relationships within Alloy.
Naturally curious with a knack for asking tough questions.
Solid understanding of core ML concepts such as supervised learning, feature engineering, and model evaluation.
A team player. You believe that big things happen when the right people are working together.

Nice-to-haves

Previous experience in financial fraud detection.
Advanced Degree (Masters or PhD) in a quantitative field.
Experience managing the end-to-end lifecycle of a technical pilot or Proof of Concept.
Experience with BI tools like Looker.
Experience with modeling on graph structures.
We're a lean team, so your impact will be felt immediately, and opportunities will grow as the company scales up. If this all sounds like a good fit for you, why not join us?

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aigomachine learningmlpythonsql

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401k

Pto

Parental Leave