Senior Data Scientist, Payments and Risk

The Senior Data Scientist role at Gusto involves collaborating with teams across Engineering, Product, and Compliance to analyze complex payment and risk data, build controls, and develop strategies that improve our services. You'll be responsible for presenting analytical results to stakeholders and working cross-functionally to solve intricate problems.

To qualify for the Senior Data Scientist position at Gusto, candidates should have at least five years of experience in a business setting, strong SQL skills, and proficiency in a scripting or statistical programming language such as Python or R. Additionally, a solid background in statistics and machine learning, along with excellent communication skills, is essential.

At Gusto, the Senior Data Scientist plays a key role in promoting a data-driven approach to product development. By leveraging rich datasets, you will provide insights that guide product direction and help product managers and engineers understand business requirements, translating analysis into actionable strategies.

A typical day for a Senior Data Scientist at Gusto involves performing in-depth analyses of payment and risk data, identifying opportunities to leverage data for product improvement, and communicating findings to various stakeholders. You'll work closely with engineering and design teams to address cross-functional challenges.

The targeted salary for a Senior Data Scientist at Gusto is between $157,000-$195,000/year in New York and CAD $131,000-$162,000/year in Toronto. Final offer amounts will depend on experience and expertise, reflecting the importance we place on attracting talented individuals.

Certainly! In your answer, highlight your SQL proficiency, mentioning specific instances where you've used it to analyze data and derive insights. Discuss how you’ve used SQL in past projects related to payments or risk analysis, and emphasize your ability to write complex queries to support data-driven decision-making.

When answering this question, discuss statistical methods like regression analysis, decision trees, or clustering techniques. Highlight how you’ve applied these methods in past roles, particularly in a payments context, explaining how they helped you identify risk signals or trends effectively.

Communicate your approach by emphasizing the importance of clear visualization and storytelling with data. Share examples of how you’ve simplified complex findings using dashboards or reports, ensuring that key insights are accessible and actionable for non-technical team members.

Share a specific example that highlights your analytical skills. Describe the problem, the methods you employed to address it, and the outcome. Stress your ability to collaborate with other teams to derive solutions that had significant impacts on business decisions.

In your response, mention resources like industry journals, webinars, and online courses that you regularly engage with to keep your skills sharp. Emphasize your interest in attending conferences or participating in data science communities to continuously learn and network.

Discuss your strategy for navigating this challenge, emphasizing open communication and collaboration. Talk about your experience in facilitating discussions to clarify the data insights, ensuring that all viewpoints are considered, with a goal of reaching a consensus based on robust data analysis.

Describe specific machine learning techniques you've utilized, such as supervised or unsupervised learning methods. Provide examples of projects where you implemented these techniques to predict outcomes or analyze patterns, explaining the results and their implications for the business.

Outline your framework for prioritizing data projects, focusing on business impact, urgency, and resource availability. Provide examples of situations where you managed competing requests effectively while ensuring timely and quality deliverables.

Share your approach to effective communication, which might include using simple language, visualizations, and storytelling to present data. Provide examples of how this strategy has helped you convey complex analyses to stakeholders in previous roles.

Articulate your passion for leveraging data to drive impactful decisions at Gusto. Discuss your ambition to contribute to the development of innovative solutions in the payments and risk domain, enhancing user experience while aligning with Gusto’s mission of empowering small businesses.