Senior Data Scientist, Payments and Risk

As a Senior Data Scientist at Gusto, you'll focus on analyzing payments and risk data, collaborating with cross-functional teams, and developing strategies that enhance our platforms. You'll be responsible for performing detailed data analysis, identifying opportunities for product improvements, and communicating results to various stakeholders, ensuring your insights shape effective product decisions.

To qualify for the Senior Data Scientist role at Gusto, you should have at least five years of experience in a business environment, strong SQL skills, and proficiency in programming languages like Python or R. Demonstrable knowledge in statistics and machine learning is also essential, along with the ability to communicate analytical findings effectively to non-technical stakeholders.

The work culture at Gusto is collaborative and inclusive, with an emphasis on teamwork across various departments. As a Senior Data Scientist, you’ll be part of a supportive environment that celebrates diverse backgrounds and encourages continuous learning. You’ll work alongside passionate individuals dedicated to empowering small businesses, making every day fulfilling and impactful.

At Gusto, you'll collaborate with an established team comprising seasoned leaders from engineering, product, design, operations, and compliance. You'll work in a dynamic setting where different expertise comes together to solve complex problems related to payments and risk, allowing you to learn and grow while contributing to meaningful projects.

Gusto is committed to the professional growth of its employees, including Senior Data Scientists. You'll have opportunities for mentorship, access to training resources, and a work environment that encourages continuous improvement and skill development. This is a place where you can take your career to the next level while making a significant impact on the company and our clients.

Gusto offers a competitive compensation package for the Senior Data Scientist position, with salaries ranging from $157,000 to $195,000 per year in New York and CAD $131,000 to CAD $162,000 in Toronto. The final offer depends on multiple factors, including your experience and expertise, ensuring we recognize and reward the talent we bring into the Gusto team.

While Gusto has physical office spaces in multiple locations, including New York and Toronto, there are flexible remote work options available. If you’re approved to work remotely, a secure and reliable internet connection is required to ensure you can seamlessly connect with the team and contribute effectively from any location.

In a complex environment like Gusto, I approach data analysis with a structured and collaborative mindset. I ensure that I understand the business context, collaborate with cross-functional teams to clarify objectives, and leverage Gusto's rich dataset to conduct thorough analyses that address specific needs and deliver actionable insights.

Certainly! In my previous role, I developed a predictive model that analyzed user transaction patterns to detect anomalies in payments. I utilized Python for data preprocessing and model building, applying various algorithms and selecting the best performer based on accuracy and recall metrics. Presenting the results to stakeholders helped implement the model into a live environment to mitigate fraud.

To communicate complex data findings to non-technical stakeholders, I focus on storytelling with data. I use clear visualizations and avoid jargon, breaking down the insights into relatable concepts that illustrate how the data connects to business goals. This approach ensures stakeholders clearly understand and can act upon the findings.

Collaboration is crucial because data science is rarely an isolated endeavor. Working alongside engineering, product, and design teams enhances the understanding of the problems at hand and leads to more comprehensive solutions. It fosters a shared vision, ensuring that data insights effectively influence product decisions and meet business objectives.

I stay updated on data science trends through a combination of online courses, webinars, and participation in industry conferences. Additionally, I follow influential data science blogs and communities, which provides fresh perspectives and insights that I can apply in my work to ensure I'm utilizing the most current tools and methodologies.

Curiosity drives my ability to explore and question data intricately. It allows me to look beyond surface-level analyses, push for deeper insights, and helps me identify unique opportunities that can lead to product enhancements. Being curious encourages continuous learning and influences a data-informed culture within the team.

In a previous project, initial analyses did not align with the stakeholders' expectations. After receiving their feedback, I revisited my approach by engaging closely with them to understand their objectives better. This collaboration resulted in adjusted methods that ultimately delivered insights that resonated more closely with their needs and enhanced the project's outcome.

I often prefer statistical methods like regression analysis, clustering, and predictive modeling when analyzing payments and risk data. These techniques help illuminate patterns and relationships within data, allowing me to provide valuable insights that inform risk assessment and improve payment processing decision-making.

When managing multiple projects, I prioritize tasks based on project deadlines, importance to business goals, and the potential impact of insights. I maintain open communication with stakeholders to align expectations and ensure that the most critical tasks that add value to Gusto’s objectives receive the attention they deserve while effectively managing my time.

One of the biggest challenges payment data scientists face is balancing the need for thorough data analysis with the demand for real-time insights and decision-making. As fraud methods become more sophisticated, delivering timely and accurate analytics while maintaining user privacy and security is crucial, pushing us to innovate continuously in our approaches.