Senior Data Scientist, Internal Operations

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 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 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, and make Klaviyo more insightful about the present and future of the business. 

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 success, finance, and sales, but that experience is not required.

You should have experience building models that are used by people to make better decisions and used by organizations to drive key outcomes. We’re focused on shipping early and often. We prefer iterative solutions that are incrementally better to a long-debated “perfect” solution.

As a Senior Data Scientist, 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.

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

What we’re looking for:

• Strong fundamental understanding and deep experience with a variety of statistical and/or machine learning algorithms (e.g. regression models, tree-based methods, large language models, clustering, neural networks) as well as ways to evaluate and validate the performance of those models
• Experience working with stakeholders directly during the course of a project and managing stakeholder relationships
• Ability to write clean, intelligible code in Python, including experience with data science tools and packages
• Enjoys the high-risk research aspect of data science, i.e. capable and excited to learn from null or negative results and iterate to a better solution
• 2+ years industry data science experience or equivalent
• Bachelor’s or advanced degree in statistics, applied mathematics, computer science or other relevant quantitative discipline, or equivalent industry experience.

Nice to have:

• Demonstrated a measurable and sizable impact with your data science work
• Strong experience analyzing data and making rigorous statements about what can or cannot be concluded
• Experience designing, implementing, and analyzing experiments

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