Mercury is hiring a
Senior Data Scientist

Summary

Join Mercury, a financial technology company, as a Data Scientist to advance our data-first approach to managing compliance and fraud risk by surfacing key metrics, building automated and reliable reporting, and enhancing our data infrastructure and understanding from end-to-end.

Requirements

• Have 4+ years of experience working with and analyzing large datasets to solve problems and drive impact, with 2+ years of experience working in compliance or fraud
• Have fluency in SQL and experience using it creatively with imperfect data
• Have consistent experience with developing dashboards using data visualization tools
• Have the ability to proactively ask questions, turn them into analyses, and make your case to various stakeholders, including senior leadership
• Be super organized and communicative. You will need to prioritize and manage projects to maximize impact, supporting multiple stakeholders with varying quantitative skill levels
• Be comfortable with decision making in a fast-paced, ambiguous environment, while demonstrating curiosity and a growth mindset

Responsibilities

• Own and manage core compliance and fraud business and operational metrics and data
• Build observability for our internal operations and risk controls efficacy through analytical deep dives and key metric dashboards
• Respond to ad hoc data requests from within Risk and from cross-functional partners in Audit, Compliance, and Product
• Partner with Risk stakeholders and cross-functional teams to identify impactful business questions, conduct deep-dive analysis, translate data insights into actionable recommendations and communicate findings to audiences at all levels to inform data-driven decisions
• Analyze historical data to identify trends, patterns, and risk factors, informing the design of risk mitigation strategies
• Collaborate with other Data Scientists and Data Engineers to build and improve data pipelines, tools, and infrastructure to streamline data collection, processing, and analysis workflows, and ensure the integrity, reliability, and security of data assets
• Leverage data models and advanced analytics techniques to design long-term solutions including enhancements of existing strategies and building new process improvements

Preferred Qualifications

• Have fluency in additional statistical programming languages (e.g. Python, R, etc.)
• Have experience building scalable data pipelines and ETL processes with DBT and understand different database structures

Benefits

• Base salary
• Equity (stock options)