Staff Data Scientist, Ads

About the role

Reddit is a community of communities. It is 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 130 million daily active unique visitors, Reddit is one of the internet's largest sources of information. For more information, visit www.redditinc.com. 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. 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. 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 and platform measurement, campaign and creative management, advertiser growth and retention, monetization, and the intersection of brand and community engagement. 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. Reddit's Ads Data Science team is looking for a highly experienced Staff Data Scientist to advance the intelligence powering the advertiser experience on Reddit. In this role, you'll take deep ownership of a high-impact problem space within advertising, specializing in measurement, identity, and signal quality. 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.

Key facts

What you'll do

Design the future of ads identity by developing and employing probabilistic models for identity resolution, defining the methodology that links on-platform and off-platform actions to maximize addressability while honoring privacy.

Advance lift methodologies and experimentation by owning the statistical rigor behind Reddit's Brand and Conversion Lift products, innovating experimental design, and developing infrastructure that supports large-scale, high-velocity, low-bias testing for advertisers.

Maximize signal for predictive performance by defining the strategy for new signal sources, mathematically quantifying the value of these signals, and collaborating with modeling teams to incorporate them into predictive models, directly improving bidding efficiency and ROAS.

Define ground truth and evaluation frameworks by solving the industry-wide challenge of validating identity and measurement, designing objective functions and truth sets used to train models and measure the incremental impact of our identity graph.

Lead through cross-functional and technical influence by collaborating deeply with engineering, product, and sales to align on strategic goals, translating insights into action, and driving execution while setting a high technical bar through mentoring and championing best practices across modeling, experimentation, and measurement.

Champion measurement integrity and data quality by establishing rigorous validation frameworks that ensure consistency, accuracy, and reliability across the advertising stack.

Partner with product and engineering to operationalize data science solutions at scale, ensuring that experiments and models are robust, performant, and aligned with Reddit's strategic priorities.

Drive advertiser-centric insights by analyzing behavior across the funnel, connecting awareness, consideration, and conversion to refine the advertising experience.

Explore and prototype advanced modeling techniques, including causal inference and multi-touch attribution, to uncover deeper understanding of campaign performance.

Act as a thought partner for stakeholders across the ads ecosystem, communicating complex findings and trade-offs to guide decision-making and strategy.

Requirements

You must have a PhD in a quantitative field such as statistics, computer science, mathematics, or a related discipline, demonstrating deep expertise in modeling and experimental methods.

You must have 5+ years of industry experience in data science or a related role, with a proven track record of delivering high-impact analytical solutions.

You must have extensive experience designing and implementing large-scale experiments and measurement frameworks in advertising contexts.

You must have strong mastery of statistical modeling, including regression, experimental design, and causal inference, with the ability to apply these methods to complex real-world problems.

You must have expert-level proficiency in Python and/or R, including experience with scalable data processing tools and modern ML libraries.

You must have a deep understanding of identity resolution, measurement infrastructure, and privacy-preserving techniques, with a track record of navigating trade-offs between accuracy and compliance.

You must have excellent communication skills, with the ability to translate technical results into actionable recommendations for both technical and non-technical audiences.

You must be comfortable operating in a fast-paced, ambiguous environment, taking initiative and driving projects forward with minimal supervision.

Nice to have

Experience with building and scaling recommendation or ranking systems.

Experience with Reddit's tech stack and advertising products.

Practical notes

This is a full-time position.

This role is remote but is based in Ontario, Canada.

This role does not require travel.

This role does not require sponsorship at this time.