Senior Data Scientist, Developer Experience

At Klaviyo, we value the unique backgrounds, experiences and perspectives each Klaviyo (we call ourselves Klaviyos) brings to our workplace each and every day. We believe everyone deserves a fair shot at success and appreciate the experiences each person brings beyond the traditional job requirements. If you’re a close but not exact match with the description, we hope you’ll still consider applying. Want to learn more about life at Klaviyo? Visit careers.klaviyo.com to see how we empower creators to own their own destiny.

About the team:

Our team is the dedicated data science resource for areas outside of R&D, such as Customer Success, Sales, and Finance, so you’ll have the chance to make an impact in a wide variety of settings and explore a wide variety of data science solutions.

Listen to our data science team podcast at https://medium.com/klaviyo-data-science and learn more about our technical culture at https://klaviyo.tech 

 

About the role:

As a Senior Data Scientist, you will expand the data science team’s impact on the internal operations and developer-facing features of Klaviyo and help raise the bar of excellence for the team. Klaviyo offers a high-growth environment across the board, and data science’s partnership with internal operations and developer experience is a shining example—the work you do will save hundreds of hours of manual work across multiple teams, directly contribute to moving key performance metrics like churn and net revenue retention, make it easier for Klaviyo customers to find the help they need when they need it, and help more businesses grow more quickly on Klaviyo by finding and using the right third-party apps. 

The ideal candidate has a strong background in data science, statistics, and machine learning. We’re looking for someone who can build, train, and deploy models, work directly with technical and non-technical stakeholders to scope projects and adjust to learnings on the fly, and learn about the areas they work in deeply enough to become an expert but quickly enough to deliver timely solutions. The right candidate will have both broad and deep knowledge: you should have a solid fundamental grasp on a large number of data science modeling and problem-solving techniques, and you should have a deep understanding and expertise in some areas as well. We’re especially interested in candidates who have experience working directly with business stakeholders in fields such as customer support, and in candidates who have experience with recommender systems, but that experience is not required.

As a Senior Data Scientist, you should have experience writing production-ready code and building models and solutions that are used in practice to drive better business outcomes. We’re focused on shipping early and often. We prefer iterative solutions that are incrementally better to a long-debated “perfect” solution. You’ll also have a strong role in mentoring other members of the team. You’ll review their math and statistics work as well as their code to ensure high quality, and you’ll share your knowledge with the team to help others learn.

This role is based in Boston, MA and requires a weekly hybrid in-office component. 

 

How you’ll have an impact:

• Work directly with stakeholders across the business to understand business problems and scope data science projects that will solve those problems
• Build models and ship automated tools that directly move key business metrics, save time spent on manual tasks, and ultimately accelerate Klaviyo’s growth
• Choose the right solution for the problem at hand rather than relying on “one-size-fits-all” approaches
• Mentor team members through statistical and code reviews, helping them learn best practices and level up their own skills

30 days 

You will have finished on-boarding including engineering and DS specific on-boarding. You will have met multiple members of the Data Science team and members of our partner teams in Customer Education, Customer Success, and Developer Experience, as well as starting to familiarize yourself with the data in those areas. You will have shipped their first small project (e.g. a small feature enhancement to existing tooling in these areas). 

60 days 

You will have begun work on your first larger mission-critical project (e.g. building a net new user-facing tool). To do this, you’ll understand the current state of that product area, work with the product manager and engineering manager for the stakeholder team to refine the idea into a well-scoped project, and develop an opinion about what is needed to tackle that project, including th