Job description
Reddit is a community of communities. It’s built on shared interests, passion, and trust and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 101M+ daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit redditinc.com.
Location: US remote-friendly
Reddit has a flexible first workforce. At Reddit we continue to grow our teams with the best talent. We’re completely remote friendly and will continue to be after the pandemic.
Advertising is Reddit’s primary revenue driver and we have an ambitious goal to turn it into a massive business. Although several large digital ad platforms already exist, advertisers are being increasingly drawn to Reddit because of our passionate communities. We believe our community-centric platform has created the opportunity for Reddit to build a highly differentiated ads business.
About the Ads Data Science Team:
The Ads Data Science team at Reddit leverages data to maximize advertiser value on Reddit through robust data foundations, metrics, and strategic insights generated through experimentation and cutting-edge DS methods.
We work on a wide range of challenging problems in the areas of ads targeting, relevance modeling, auction optimization, measurement, and user experience. We are a highly collaborative team of passionate data scientists and engineers who are constantly pushing the boundaries of what’s possible with machine learning and statistical modeling.
About the Role:
Reddit’s Ads Data Science team is looking for a highly experienced Staff Data Scientist to advance the intelligence powering our two-sided ads marketplace. In this role, you’ll take deep ownership of a high-impact problem space within advertising, specializing in a critical area such as ad auctions, measurement, advertiser experience, performance optimization, ad formats, etc.
This is a high-impact, high-autonomy role where you’ll influence strategic direction, set a high technical bar, and drive cross-functional initiatives across one or more critical focus areas in the Ads organization.
Responsibilities:
- Drive Strategic Impact Across Ads Domains: Take end-to-end ownership of complex problem spaces such as auction optimization, auto-bidding, ad creative performance, personalization, and targeting.
- Develop Advanced Models and Frameworks: Build and deploy predictive models, optimization frameworks, and decision-support systems that power Reddit’s ad platform and marketplace health.
- Translate Ambiguity into Measurable Outcomes: Define core business and performance metrics, and design robust methodologies to measure the impact of product and modeling changes on advertiser ROI and user experience.
- Lead Through Cross-Functional and Technical Influence:: Collaborate deeply with engineering, product, and sales to align on strategic goals, translate insights into action, and drive execution. Set a high technical bar by mentoring others and championing best practices across modeling, experimentation, and measurement.
- Drive Innovation in Ad Systems: Leverage causal inference, auction theory, and large-scale data systems to solve novel problems in a rapidly evolving ad marketplace.
Qualifications:
Required:
Master’s or Ph.D. in Statistics, Computer Science, Economics, Operations Research, or a related quantitative discipline.
For M.S. holders: 10+ years of industry experience in applied science, data science, or machine learning engineering roles
For Ph.D. holders: 6+ years of relevant experience applied science, data science, or machine learning engineering roles
Demonstrated expertise in at least one of the following:
- Auction Design & Optimization
- Targeting, Personalization & Lookalike Modeling
- Ads Creative & Format Evaluation
- Measurement & Experimentation at Scale
Advanced proficiency in statistical programming (Python or R) and SQL.
Experience with machine learning or optimization techniques
Strong understanding of experimental design, causal inference, or A/B testing methodologies.
Exceptional problem-solving and communication skills, with a track record of influencing product and engineering partners.
Experience working in fast-paced, ambiguous environments with cross-functional teams.
Benefits:
- Comprehensive Healthcare Benefits
- 401k Matching
- Workspace benefits for your home office
- Personal & Professional development funds
- Family Planning Support
- Flexible Vacation (please use them!) & Reddit Global Wellness Days
- 4+ months paid Parental Leave
- Paid Volunteer time off
#LI-Remote
Pay Transparency:
This job posting may span more than one career level.
In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/.
To provide greater transparency to candidates, we share base pay ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.
The base pay range for this position is:
$217,000—$303,900 USD
Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.
