Data Scientist, Growth

San Francisco, California; New York City

Applications have closed

Notion

A new tool that blends your everyday work apps into one. It's the all-in-one workspace for you and your team.

View company page

About Us:

We're on a mission to make it possible for every person, team, and company to be able to tailor their software to solve any problem and take on any challenge. Computers may be our most powerful tools, but most of us can't build or modify the software we use on them every day. At Notion, we want to change this with focus, design, and craft.

We've been working on this together since 2016, and have customers like Pixar, Mitsubishi, Figma, Plaid, Match Group, and thousands more on this journey with us. Today, we're growing fast and excited for new teammates to join us who are the best at what they do. We're passionate about building a company as diverse and creative as the millions of people Notion reaches worldwide.

About The Role:

Notion’s mission is to make toolmaking ubiquitous. We are rapidly growing our business to empower every individual to build their own tools, block by block. The Growth Data Science team aims at accelerating product growth at every step of the user journey to ensure you get the best value out of Notion. As an early member of the growth data science team, you'll be instrumental in setting the roadmap for how these teams work together and then doing the hands-on work to execute against it. There will be significant variation from one day to the next, but whether you're exploring where we see the biggest opportunity to improve user experience, what a successful Notion account looks like, building out a core activity data set, or running experiments to evaluate the success of a key feature launch, you'll absolutely impact the development of Notion.

What You'll Achieve:

  • You will apply your expertise in statistical inference, data mining, and the presentation of data to see beyond the numbers and understand how our users interact with Notion
  • You will dive into ambiguous areas, define problems and opportunities for the team to work on the next influential project
  • You'll design the right set of experiments or analyses to evaluate the success of new features
  • You'll partner closely with a product, engineering, and marketing pillar at every step of the development process, driving forward data science and analytics work in that area.
  • You'll work with your teams to determine both north star and operational metrics, and build and maintain the dashboards that those teams rely on for monitoring progress and making key decisions.
  • You'll influence your product roadmap by communicating your findings with the rest of the company, and driving and verifying change in our product and business. (Insights are useful. Impact is even better!)

Skills You'll Need to Bring:

  • You have spent meaningful time as a data scientist partnering with product, engineering and ideally with growth teams. You can draw on that experience to identify where data can have the most impact and clearly communicate to your partner teams what that impact is.
  • You are comfortable with ambiguity and uncertainty
  • You have expertise in SQL and at least one scripting language (ideally Python or R).
  • You know how to use statistical inference and experimentation to drive actionable recommendations.
  • You have experience building predictive models, and you know how to evaluate their effectiveness.
  • You are comfortable transforming raw data to build your own data sets if the measure you need doesn't exist yet.
  • You have a bias for using the right tools to get a job done with maximum efficiency. You have experience making tradeoffs between speed and accuracy.

Nice to Haves:

  • You have worked at a fast-growing start-up.
  • You have experience at a B2B SaaS company.
  • You have been a Technical Lead or Manager within Data Science teams previously
  • You have helped design processes that data science teams use to collaborate with their product and engineering peers.
  • You have a track record of acting as a thought partner to product or engineering leaders, driving strategic decisions on these teams using data.

We hire talented and passionate people from a variety of backgrounds because we want our global employee base to represent the wide diversity of our customers. If you’re excited about a role but your past experience doesn’t align perfectly with every bullet point listed in the job description, we still encourage you to apply. If you’re a builder at heart, share our company values, and enthusiastic about making software toolmaking ubiquitous, we want to hear from you.

Notion is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex (including pregnancy, childbirth, or related medical conditions), marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or other applicable legally protected characteristic. Notion considers qualified applicants with criminal histories, consistent with applicable federal, state and local law. Notion is also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, please let your recruiter know.

#LI-Onsite

* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Tags: Data Mining Engineering Python R SQL Statistics

Perks/benefits: Flex vacation Startup environment

Region: North America
Country: United States
Job stats:  11  1  0
Category: Data Science Jobs

More jobs like this

Explore more AI, ML, Data Science career opportunities

Find even more open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general - ordered by popularity of job title or skills, toolset and products used - below.