Staff Data Scientist

Job not on LinkedIn

🔥 0 minutes ago

🌐 United States, Canada – Remote

🇺🇸 United States – Remote 🇨🇦 Canada – Remote

🏄 California, New York, +1 more states – Remote

🏄 California – Remote 🗽 New York – Remote 🌲 Oregon – Remote

💵 $239k - $298.8k / year

⏰ Full Time

🔴 Lead

📊 Data Scientist

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

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Mercury

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2017

💳 Fintech

🏦 Banking

☁️ SaaS

Fintech • Banking • SaaS

Mercury is a software-driven fintech that provides business and personal banking products built for startups and small to mid-size companies. Its platform offers business checking and savings, Treasury products, business credit cards and spend management, payments and invoicing, accounting integrations and AI-powered automations, plus APIs and developer tools. Mercury partners with FDIC-insured banks to offer deposit protection, emphasizes virtual cards, granular spend controls, and workflow automations for teams, agencies, ecommerce brands, VC funds, and crypto businesses. The product is positioned as an all-in-one banking and finance platform delivered through a modern app and API.

📋 Description

• Build, validate, and deploy machine learning models to identify and prevent fraud in real time • Support model reproducibility and robustness through documentation, testing, and monitoring • Ensure data quality and reliability across pipelines and tools • Collaborate with Risk Strategy to ideate on model inputs and applications • Collaborate with Engineering to optimize deployment and observability • Act as a technical lead prototyping, iterating on, and codifying best practices • Bring the rest of the team along on best practices • Support Mercury’s Risk team in detecting, monitoring, and mitigating first- and third-party fraud and monitoring customers for financial crime risk • Collaborate across product, engineering, and risk to protect customers and the financial system

🎯 Requirements

• 7+ years of experience working with and analyzing large datasets to solve problems and drive impact, with 5+ years of ML experience • Proficiency in SQL and experience using it to understand and manage imperfect data • Proficiency in Python and experience with statistical modeling and machine learning • Experience deploying and monitoring machine learning models in production • Comfort working in a fast-paced environment with evolving priorities • Demonstrated ability to lead and empower others, delivering not just on your own work, but upleveling those around you • The ability to drive strategic alignment between teams with differing roadmaps, timelines, or architectures • 1+ years of relevant risk experience • Familiarity with LLMs or other GenAI and how they can be applied to risk or fraud detection • Experience with modern data tools for pipelines and ETL (e.g., dbt) • Experience with model governance as required in finance or other regulated industries • Experience building zero-to-one solutions in ambiguous or greenfield problem spaces

🏖️ Benefits

• Equity (stock options/RSUs) • Benefits • Competitive total rewards package • Reasonable accommodations throughout the recruitment process