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Treehouse

Data Scientist II

Treehouse, Oklahoma City, Oklahoma, United States,


As a Data Scientist, you will be a technical co-owner of the data science business health tooling at Klaviyo. One of Klaviyo’s core values is ownership—the ability to bias toward action, think one step ahead of problems you might face, and generally just get things done—and this role is a shining example. The solutions you deliver and research you complete for the business health tools will directly contribute to our go-to-market teams and improve the success of our customers as well as help Klaviyo meet our revenue, churn, and sales goals.

The ideal candidate has a strong background in data science, statistics, and machine learning, with a heavy emphasis on using these tools to solve business problems. We’re looking for someone who can build, train, and deploy models, work directly with both technical and non-technical stakeholders to scope projects and adjust to new information on the fly, and learn about the areas they work in deeply enough to become an expert but quickly enough to deliver timely solutions. As a technical co-owner of the data science business health tooling, you will be expected to be able to speak about your technical solutions to stakeholders within the business, so communication skills are essential.

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

Responsibilities

Co-own a strategically crucial and high-impact technical area

Work directly with stakeholders across the business to understand business problems and scope data science projects that will solve those problems

Conduct research, build models, and ship solutions that make our forecasting system better, more reliable, and more user-friendly

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

Qualifications

2+ years industry experience as a data scientist with 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

Bachelor’s or advanced degree in statistics, applied mathematics, computer science, or other relevant quantitative discipline, or equivalent industry experience.

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 and excited to learn from null or negative results and iterate to a better solution

The pay range for this role is listed below. Sales roles are also eligible for variable compensation and hourly non-exempt roles are eligible for overtime in accordance with applicable law. This role is eligible for benefits, including: medical, dental and vision coverage, health savings accounts, flexible spending accounts, 401(k), flexible paid time off and company-paid holidays and a culture of learning that includes a learning allowance and access to a professional coaching service for all employees.

Base Pay Range For US Locations: $123,200—$184,800 USD

About KlaviyoAt 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.

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