Software Engineer (Data Science) at Klaviyo

We love programming and the excitement that comes with building something people use. We are the kind of people that love talking to users and can find the balance between solving a problem quickly and thinking about how your code will work in the future. We love to move fast, keep learning and get stuff done.

Our data science team takes ideas from inception to new machine learning-powered features that ship to our hundreds of thousands of users. You’ll be central to creating features that help our customers learn and grow from their data. For this role, we’re looking for people who have developed split brains--software engineers who have become great at writing machine learning code or data scientists who have become great software developers.

Technologies we use (not comprehensive!):

• Python
• Numpy, Scipy, Pandas
• Aurora, Cassandra, Kafka
• HTML, JavaScript, React
• SageMaker

Klaviyo is growing fast and we have openings for all skill levels across all of our teams. Learn more about our engineering culture at https://klaviyo.tech and listen to our data science team podcast at https://medium.com/klaviyo-data-science

How you will make a difference:

• Build products that enable our customers to grow faster using data science.
• Develop machine learning models and pipelines for research and production.
• Analyze large data sets (we’re collecting billions of individual actions every month).

Who You Are:

• 4+ years of software engineering experience in a SaaS environment
• Experience mentoring or managing Engineers 
• Have experience implementing machine learning models, data pipelines and testing frameworks for research and production use.
• Have demonstrated a measurable impact based on the models you’ve created. It’s not always easy getting a model correct, we love talking about places we got stuck and work as a team to think through ideas that could unblock us.
• Have experience processing cloud-scale data using parallel, elastic, streaming and similar techniques.
• Enjoy tuning and validating machine learning models and take a rigorous approach.
• Understand how to profile code and optimize performance.
• Aspire to correctness (e.g. in your code, in drawing conclusions from data)
• Have a bachelor’s or advanced degree in computer science, applied math, statistics or other relevant quantitative discipline, or equivalent industry experience.