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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning-focused Data Scientist - **Company:** Mercury - **Location:** United States - **Salary:** $239,000.0 - $298,800.0 - **Contract:** Permanent contract - **Skills:** Data Analysis, Extract Transform Load (ETL), Fraud Prevention and Detection, Python (Programming Language), Machine Learning, SQL Databases, Large Language Models - **Published:** September 4, 2026 - **Apply:** https://www.dice.com/job-detail/d274fcf6-f4e5-4862-9813-154038976b81 ## About the Role * 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 Ideally you also have: * 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 ## Description To that end, we are hiring a Machine Learning-focused Data Scientist to support our Risk team. This team is responsible not only for detecting, monitoring, and mitigating both first- and third-party fraud but also ensuring we know and understand our customers while monitoring their behavior for financial crime risk. You'll play a key role in strengthening our fraud defenses while ensuring that Mercury continues to deliver a smooth and trustworthy banking* experience. This is an opportunity to join Mercury at a pivotal moment in our growth. You'll be working on some of the most critical challenges facing the business and collaborating across product, engineering, and risk to protect our customers and the financial system at large. Here are some things you'll do on the job: * Build, validate, and deploy machine learning models to identify and prevent fraud in real time * Support the reproducibility and robustness of said models 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 and with Engineering optimize deployment and observability * Act as a technical lead prototyping, iterating on, and codifying best practices - and bringing the rest of the team along ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [Detecting Money Laundering with AI](https://www.wearedevelopers.com/videos/111-detecting-money-laundering-with-ai) - [Fault Tolerance and Consistency at Scale: Harnessing the Power of Distributed SQL Databases](https://www.wearedevelopers.com/videos/1146-fault-tolerance-and-consistency-at-scale-harnessing-the-power-of-distributed-sql-databases) - [How Machine Learning is turning the Automotive Industry upside down](https://www.wearedevelopers.com/videos/61-how-machine-learning-is-turning-the-automotive-industry-upside-down) - [What non-automotive Machine Learning projects can learn from automotive Machine Learning projects](https://www.wearedevelopers.com/videos/397-what-non-automotive-machine-learning-projects-can-learn-from-automotive-machine-learning-projects) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it)