At
Datadog, we’re on a mission to build the best monitoring platform in
the world. We operate at high scale—trillions of data points per day—and
high availability, providing always-on alerting, visualization, and
tracing for our customers' infrastructure and applications around the
globe.
Our engineering culture values pragmatism, honesty, and simplicity to
solve hard problems the right way. We need you to design and build
machine learning-powered products that help our customers learn from
their data and make better decisions in real-time.
You will have a fantastic team of data engineers to support you, a
collaborative environment to encourage your work, and the best
technologies for performing data science at high scale in your toolkit.
Join us to build powerful, intelligent data systems. In a typical week as a Data Scientist, you might:
- Present the latest academic research papers to your team.
- Research and benchmark the latest algorithms that can be used for our particular use-cases.
- Apply machine learning algorithms and statistical techniques to build new product features.
- Deploy a new feature to production, instantly affecting customers with your work.
- Mentor other data scientists on your team.
- Explore and find meaning in extremely high volumes of data.
- Investigate and fix a production issue from a service your team owns.
Requirements
- You have backend programming experience in one or more languages.
- You care about code simplicity and performance.
- You have mastered working with data in a language such as Python, R, or Julia.
- You can explain complex ideas and algorithms in understandable ways.
- You have significant experience applying machine learning to real business problems.
- You have a BS/MS/PhD in a scientific field or equivalent experience.
- You want to work in a fast, high-growth startup environment and thrive on autonomy.
- You are fluent with SQL / relational algebra.
Bonus points
- You’ve done data science at high scale with tools like Hadoop and Spark.
- You’ve written production data pipelines.
- You’re familiar with time series analysis.
