Senior Data Scientist - Banking

## About the Role As a Senior Data Scientist at Mercury, you will play a critical role in shaping the future of financial infrastructure for startups and growing businesses. You will work closely with cross-functional teams, including Product, Engineering, Design, Underwriting, and Operations, to develop and implement data-driven solutions that drive business growth and informed decision-making. Your expertise in data science and analytics will be instrumental in helping Mercury build a data-informed culture that enables teams to move quickly, measure what matters, and invest intelligently. The role of a Senior Data Scientist at Mercury is multifaceted and challenging. You will be responsible for analyzing complex data sets, developing predictive models, and creating data visualizations to communicate insights to stakeholders. You will also work closely with product managers to develop and refine product roadmaps, and with engineers to design and implement data pipelines and architectures. Mercury is committed to building a diverse and inclusive team, and we are looking for candidates who share our values and are passionate about using data science to drive business impact. If you are a motivated and experienced data scientist who is looking for a new challenge, we encourage you to apply. ## What You Will Do - Develop and maintain complex data models and architectures to support business decision-making - Analyze large datasets to identify trends, patterns, and insights that inform product development and business strategy - Design and implement A/B testing and experimentation frameworks to measure the impact of product changes - Collaborate with cross-functional teams to develop and refine product roadmaps and priorities - Develop and maintain data visualizations and reports to communicate insights to stakeholders - Work closely with product managers to develop and refine product requirements and specifications - Design and implement data pipelines and architectures to support data analysis and modeling - Develop and maintain predictive models to forecast key business outcomes - Collaborate with engineers to design and implement data-driven solutions - Develop and maintain documentation of data models, architectures, and analysis results - Stay up-to-date with industry trends and emerging technologies in data science and analytics ## What We Are Looking For - 7+ years of experience working with large datasets to drive product or business impact in data science or analytics roles - Strong technical skills in programming languages such as Python, SQL, and R - Experience with data modeling and architecture, including data warehousing and ETL processes - Strong understanding of machine learning and statistical modeling techniques, including supervised and unsupervised learning - Experience with data visualization tools such as Tableau, Power BI, or D3.js - Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams - Experience with agile development methodologies and version control systems such as Git - Strong business acumen and understanding of financial concepts and principles - Experience working in a fast-paced and dynamic environment, with the ability to adapt quickly to changing priorities and requirements ## Nice to Have - Experience working on cards or credit products, with familiarity with card economics and lifecycle concepts - Experience developing quantitative pricing models or engines, including dynamic pricing and incentive optimization - Experience working with cloud-based data platforms such as AWS or GCP - Experience with natural language processing or text analysis techniques - Experience working in a remote or distributed team environment ## Benefits and Perks - Competitive salary and equity package - Comprehensive health, dental, and vision insurance - Flexible PTO and vacation policy - Remote work stipend and equipment allowance - Professional development and training opportunities - Access to cutting-edge technologies and tools - Collaborative and dynamic work environment - Opportunity to work on complex and challenging problems - Recognition and reward for outstanding performance and contributions

- Tip: Make sure to highlight your experience working with large datasets and developing predictive models in your application materials.

• Tip: Be prepared to discuss your technical skills and experience with data modeling and architecture during the interview process.
• Tip: Show examples of your data visualizations and reports, and be prepared to walk the interviewer through your thought process and methodology.
• Tip: Research Mercury's products and services, and be prepared to discuss how your skills and experience align with the company's goals and objectives.
• Tip: Be prepared to discuss your experience working in a remote or distributed team environment, and how you stay connected and collaborative with colleagues.
• Tip: Don't be afraid to ask questions during the interview process, and be prepared to discuss your career goals and aspirations.
• Tip: Make sure to proofread your application materials carefully, and be prepared to provide examples of your work and experience.