{"id":163512,"url":"https://alion.io/job/alloy-senior-data-scientist","title":"Senior Machine Learning Engineer","company":{"id":58425,"name":"Alloy","domain":"alloy.com","url":"https://alion.io/company/alloy-com","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"A","score":92,"open_postings":8,"ghost_share":0,"stale_share":0.125,"repost_share":0,"time_to_fill_p50_days":89,"computed_at":"2026-10-17T05:46:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["New York, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":159000,"max":230000,"currency":"USD","period":"year","gross":null,"usd_annual":230000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Looker","optional":true}],"status":"live","first_seen_at":"2026-04-07T21:49:04Z","employer_posted_date":"2026-09-24","last_verified_at":"2026-10-17T08:48:56Z","board_verified":true,"closed_at":null,"days_open":192,"trust":{"level":"ok","repost_count":0,"flags":[],"days_open":192},"description":"Alloy is where you belong!\nAlloy 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.\nThrough 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.\nCheck out our investors and read more about us here.\nAbout the team\nThe 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.\nYou will work on advancing our core models while also partnering directly with customers to drive strong outcomes from fraud studies.\nAlloy operates in a hybrid work environment. We look to foster collaboration and community by having our local employees onsite three days a week.\nWhat you'll be doing\nContribute to the design, training, and evaluation of machine learning models that power Alloy’s fraud detection capabilities.\nDevelop testing plans, metrics, performance reports, and translate findings into actionable recommendations.\nSupport production ML workflows, including feature generation, model training, and monitoring, to ensure models remain accurate and reliable at scale.\nDocument findings and communicate insights to internal teams, contributing to shared learning and continuous improvement.\nMaintain up-to-date model documentation and support Alloy’s model governance processes to ensure transparency and compliance.\nStay current with industry trends in applied ML and fraud detection, and contribute to Alloy’s mission of making financial services safer and more accessible.\nWho we’re looking for\nAlways building with end-solution in mind. \nAble to communicate complicated concepts to a non-technical audience without diluting the complexity of the work.\nAble to build strong cross-functional relationships within Alloy.\nNaturally curious with a knack for asking tough questions.\nSolid understanding of core ML concepts such as supervised learning, feature engineering, and model evaluation.\nA team player. You believe that big things happen when the right people are working together.\nA fast learner\nHumble. Mistakes happen and owning them helps us learn and move on quickly\nYou have:\n8+ 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.\nExpertise in working with highly imbalanced datasets and building production-grade Machine Learning models with specific interest in tree-based models.\nAdvanced proficiency in scripting languages like Python and querying languages like SQL\nProven ability to wrangle and think thoughtfully about data at scale (processing billions of records).\nExperience developing metrics and dashboards.\nAble to communicate their findings effectively to technical and nontechnical members\nSomeone who embodies our shared Alloy values: be bold, get scrappy, collaborate, and celebrate our differences.\nYou have experience in a highly analytical role in fast-paced environments\nMust be local to Greater New York City.\nNice to Haves:\nPrevious experience in financial fraud detection.\nAdvanced Degree (Masters or PhD) in a quantitative field.\nExperience managing the end-to-end lifecycle of a technical pilot or Proof of Concept.\nExperience with BI tools like Looker.\nExperience with modeling on graph structures.\nWe'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?\nAlloy 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!\nThis position has a salary range of $159,000, to $230,000.\nBenefits and Perks \nUnlimited PTO and flexible work policy\nEmployee stock options\nMedical, dental, vision plans with HSA (monthly employer contribution) and FSA options\n401k with 100% match up to 4% of annual employee compensation \nEligible new parents receive 16 weeks of paid parental leave \nHome office stipend for new employees\nAnnual Learning & Development annual stipend\nWell-being benefits include access to ClassPass, OneMedical, UrbanSitter, and Spring Health \nHybrid 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.\nHow to apply\nApply right here! You've found the application!\nAlloy 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.\nAll 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.","description_format":"text","description_chars":6913,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":false},"security_clearance":false,"languages":[]},"benefits":["401k plan","Equity","Flexible schedule","Home office","Hybrid work","Parental leave","Stock options","Unlimited PTO"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Fraud Detection","Identity Management","RegTech, AML & Compliance"],"lifecycle":[{"event":"open","at":"2026-04-07T21:49:04Z"}],"visa":[],"liveness":{"score":18,"band":"cold","label":"Long shot","p_open":1,"p_active":0.643,"p_room":0.28,"age_days":192,"expected_fill_days":89,"reasons":["conf:0","win:tail","crowd:"],"computed_at":"2026-10-17T05:46:00Z"},"pay":{"stated_usd_annual":230000,"is_top_pay":true},"html_url":"https://alion.io/job/alloy-senior-data-scientist","json_url":"https://alion.io/job/alloy-senior-data-scientist.json","meta":{"generated_at":"2026-10-17T10:09:28Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":13286,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-18T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":58425},"rest":"https://alion.io/mcp/rest/get_company?id=58425"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Falloy-senior-data-scientist"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Falloy-senior-data-scientist"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Falloy-senior-data-scientist"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/alloy-senior-data-scientist\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Falloy-senior-data-scientist"}]}