Data Scientist at Donut

At Donut we are on a mission to create more trusting, collaborative, and successful work relationships. We believe genuine relationships are the key to being engaged, happy, and successful at work.

Donut came together over a shared passion to help people connect, and the insight that strong relationships at work are the bedrock of a successful team. Employees who feel socially connected to their coworkers express greater individual purpose and fulfillment, less workplace loneliness and isolation, and improved performance and productivity. We are building a company that embodies those ideals while instilling them in others.

How we work:

Our small, fully remote product, design, and engineering team is filled with empathetic and caring individuals dedicated to unlocking the power of human connection. We’re organized as smaller (three to six person) pods that evolve a few times a year based on our objectives and the addition of new talent.  We build new features together in two-week sprints and this cadence aligns with other company rituals. Our core connection hours are 11 a.m. – 5 p.m. ET / 8 a.m. – 2 p.m. PT.

About the role:

We are looking for our first Data Scientist to join our team. To-date, basic data analysis activities have been conducted in Periscope Data dashboards and in Mixpanel by a mix of engineers and people in operations and product/design. As Donut deepens its product capabilities, we are eager to add more and better data-derived insights to our approach for user-centric product development. 

This role is all about high impact. If you’re eager to guide big choices, pick low-hanging fruit, and see user and business outcomes quickly, we’ll be a great match. If you’re primarily interested in theoretical ML or deep learning, then Donut is probably not at the right stage for you. This is a chance to apply your analytical craft with a team that respects your work. 

Like many startups, we have a near-endless backlog so optimizing prioritization is essential. You’ll have the chance to build things right from the ground up: to make crucial foundational decisions to better incorporate discrete signals in our product development process.  

You will report to the VP of product but your scope will follow opportunities wherever they are. This may include analysis, for example, higher in the marketing funnel or overlapping with our customer support organizations’ scopes. We’re a collaborative company so doing the right things for our users is more important than rigid boundaries of roles. (Just for clarity: this is not a euphemism for being immature, disorganized, or chaotic. :)


What you’ll do:

Interpret data, generate hypotheses, draw conclusions, and help establish and refine metrics and dashboards. 
Act as an internal consultant for product/design/engineering, marketing, customer, and other operations teams, translate business problems into data analyses and collaborate with counterparts to recommend actions and help prioritize product and engineering work.
Work closely with engineering to ensure the scalability – accuracy, availability, and integrity – of Donut’s data pipeline while also leading foundational choices for data. 
Consider trade-offs and select optimal, maintainable paths. This includes data engineering and infrastructure considerations like evolving the data warehouse and selecting other tools and methods. 
Advance a healthy, connected, and continuous learning culture across all functional teams.



About you:


Data Expert. You’re passionate about data, analysis, trends, and metrics applied to growth stage businesses. This may come from a background of undergraduate or graduate study in fields such as math, computer science, operations research, economics, statistics, engineering, or other quantitative fields—or equivalent experience in non-academic work (no degree is required for this role). You have at least three years of industry experience in user-facing data science or analytics, especially for SaaS businesses or e-commerce funnels. 

Excited to Execute. Eager to get your hands dirty with potentially messy data to uncover product opportunities. Experience working with databases, SQL database queries development and analysis, and potentially other scripting/programming languages (like Python or R). 

Foundation Builder. Very comfortable collaborating with engineers to enable access to not-yet available data: creating and improving data engineering / ETL (extract-transform-load), and data infrastructure.

Versatile. Experience in developing analytical models to solve ambiguous business problems, especially across multiple teams or product areas. Knowledge of applied statistical methods (modeling, causal inference), experiment design (hypothesis, A/B and multivariate testing), measurement, and program evaluation. Nice to have: experience with simulation and optimization techniques.

Storyteller. Have distilled interesting insights into compelling, succinct narratives and visualizations that can influence product development and decision making at all levels, technical and non-technical: from customer support and engineering ICs to executive team members and investors.



Our hiring process:

We’re a small team so it may take us a little more time to review your application. Thank you for your patience and understanding!

The salary range for this role is $125,000-$175,000 annually.


Benefits (full-time US employees)


- Medical, Dental, and Vision benefits
- 401(k) with company match
- Diversity, Equity, and Inclusion program
- Unlimited paid time off and 10 company holidays
- Paid family leave
- Monitor stipend
- Home office stipend
- Mental health benefit

About Donut

Donut has made millions of connections and is used by over 20,000 companies. Donut has raised $12M in venture-funding from investors including Accel, Bloomberg Beta, FirstMark, and Slack Fund: https://techcrunch.com/2020/10/29/donut-watercooler/

Donut is an equal-opportunity employer and we value diversity, equity, and inclusion at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.