Full Stack Data Scientist
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.
Klaviyo’s data science team builds the tools that allow entrepreneurs, creators, and businesses to personalize, optimize, and automate communication with audiences based on first party data. The full stack data scientist position is a multidisciplinary role that combines data and algorithm discovery, UX design, and software engineering. We're looking to find high slope individuals who have backgrounds in math, statistics, data science, or other technical fields who want to learn the craft of bringing data science methods into production. Full stack data scientists learn the software engineering skills they need to build data science features from infrastructure to front end. For this role, prior software experience is not required, but a strong interest in learning it is a must. In this role, you will work alongside machine learning engineers, data scientists, product managers and designers in small teams. These teams build and maintain features in their product areas, such as automated A/B testing, personalized suggestions, account benchmarking, product recommendations and content generation. Technologies You Will Use and Learn
- Python
- Numpy, Scipy, Pandas
- Aurora, Cassandra, Kafka
- HTML, JavaScript, React
- Terraform, AWS Batch
How You'll Make a Difference
- Build products that enable hundreds of thousands of businesses to grow faster using data science
- Test algorithms and techniques on large and small data sets - audience sizes on Klaviyo span approximately seven orders of magnitude
- Develop UX experiences that let anyone understand and leverage statistical techniques
- Engineer data systems that let non-technical users make decisions with their first party data in real time
- Analyze the impact of the features you ship to monitor their performance
Who You Are
- You possess a strong fundamental understanding of statistics and data science techniques (e.g. regressions, decision trees, k-means clustering, neural networks).
- You are excited to build out the UX and backend needed to bring a data science model into the hands of users.
- You are capable of analyzing data and making rigorous statements about what can or cannot be concluded.
- You dig into the details and interconnected systems when working on projects or analyzing the effects of an experiment.
- You aspire to correctness (e.g. in your code, in drawing conclusions from data)
- You have a bachelor’s or advanced degree in computer science, applied math, statistics or other relevant quantitative discipline, or equivalent industry experience.
- You are excited to apply your potential to grow technical skills and build an awesome product.
Get to Know Klaviyo
Klaviyo is a world-leading marketing automation platform dedicated to accelerating revenue and customer connection for online businesses. Klaviyo makes it easy to store, access, analyze and use transactional and behavioral data to power highly-targeted customer and prospect communications. The company's hybrid customer-data and marketing-platform model allows companies to grow by fostering direct relationships with customers, without giving up their valuable data to popular big-tech ad platforms. Over 265,000 innovative companies like Unilever, Custom Ink, Living Proof and Huckberry sell more with Klaviyo. Learn more at www.klaviyo.com.
Klaviyo is committed to diversity and to a policy of equal employment opportunity and non-discrimination. We do not discriminate on the basis of race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, sexual orientation or any other characteristic protected by applicable law.