Lead Data Scientist / Applied Statistician

About the Job:

We are currently looking for a Lead Data Scientist to join our Decision Science Products team. As a lead data scientist you will help us choose and develop the best statistical methods for various data and decision science products. The decision science products teams currently own experimentation, LaunchDarkly’s second largest product, and are developing additional products that rely heavily on statistics, especially sequential testing and Bayesian optimization. We're looking for someone who can work efficiently as the first, full-time data scientist on the decision science team getting solutions from concept to production.

Our data platform processes events from over twenty billion feature flag evaluations, and billions of experimentation metrics events daily. The core technologies we use daily include Golang, Scala, Kinesis, and Flink. As a data scientist you will oversee be responsible for finding the appropriate statistical methods for various problems in our product space, and working with data engineers to implement those solutions at scale.

Your work will be used by companies from small to large, across multiple industries, allowing them to make the best business decisions possible.

• Build and expand our data and decision science products
• Design statistical solutions for new products and evolving customer needs
• Collaborate with product team to influence and deliver user-facing features
• Partner with customers to solve diverse data challenges using our products
• Promote  statistics standards, tooling, and processes
• Opportunity to work on industry or academic papers for new methodologies
• Opportunity to build out a team of data scientists
• Opportunity to help educate customers via blog posts, office hours, etc.

On day one, you should have:

• Advanced degree in Statistics, Mathematics, Physics, Economics or related quantitative field
• Proven experience and fluency probability and statistics
• Experience building experimentation tools
• Appreciation for both frequentist and Bayesian statistics
• Strong communication skills, a positive attitude, and empathy
• You hold yourself and others to a high bar when working with statistics
• You value high code quality, reproducibility, and other data engineering best practices

• Experience with sequential testing

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