About this role.
Reddit seeks a Staff Data Scientist to drive the intelligence powering its ads measurement, identity, and signal quality. This high-impact role involves designing identity resolution models, advancing lift methodologies, and defining strategies for new signal sources. The ideal candidate possesses an advanced degree, deep ads ecosystem knowledge, and expertise in measurement, identity, or predictive modeling. You will work autonomously, lead cross-functional initiatives, and mentor others to raise the technical bar.
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Cover letter sample
Dear Hiring Team,
I am thrilled to apply for the Staff Data Scientist position at Reddit. With over a decade of experience in applied data science and a PhD in Statistics, I have led large-scale experimentation and identity resolution initiatives that directly improved advertising performance and measurement accuracy. My expertise in causal inference, machine learning, and cross-functional leadership aligns perfectly with Reddit's mission to build trusted, privacy-centric ad solutions.
I am particularly excited by the opportunity to shape Reddit's ads measurement infrastructure and drive strategic direction on signal quality. I look forward to bringing my technical rigor and collaborative spirit to Reddit's mission-driven team.
Sample interview questions
I would start by clearly defining the addressability goals and privacy constraints. Using a probabilistic approach, I would build a graph-based model with features like device IDs, cookies, and user behavior, applying differential privacy or k-anonymity where needed. I would validate the graph using ground truth datasets and measure the incremental lift in ad performance, iterating with engineering to ensure scalability and compliance.
In a previous role, I led the transition from simple A/B tests to sequential testing with continuous monitoring, reducing false positives in a high-velocity experimentation platform. I implemented variance reduction using CUPED, managed multiple testing corrections, and built guardrail metrics to track user harm. This improved the accuracy and speed of decision-making across dozens of concurrent experiments.
I would define the counterfactual: compare model performance with and without the new signal using offline evaluation on historical data, with metrics like lift in ROC-AUC or calibration. Then I would run simulation tests to measure downstream impact on bidding efficiency and ROAS. I would also calculate the cost of acquiring and processing the signal to determine net value.
I would use a combination of approaches, including purchase data from advertisers (deterministic when available), panel-based ground truth, and synthetic benchmarks. For evaluation, I would design objective functions that balance precision and recall for identity linkage, and use holdout sets to measure incremental impact on conversion lift. I would iterate by comparing model outputs against known true matches and analyzing failure modes.
I would start by understanding their goals and constraints, then use data to demonstrate the value, such as showing improved ROAS or reduced measurement bias. I would create a clear implementation roadmap, involve engineers early in design, and communicate results through simple, compelling narratives. I would also provide tooling and documentation to lower friction, and champion wins through metrics reviews and leadership updates.
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.
Responsibilities:
- Design the Future of Ads Identity: Develop/employ probabilistic models for identity resolution. Design the methodology that links on-platform and off-platform actions to maximize addressability while honoring privacy.
- Advance Lift Methodologies & Experimentation: Own the statistical rigor behind Reddit’s Brand and Conversion Lift products. Innovate experimental design and develop infrastructure that supports large-scale, high-velocity, low-bias testing for advertisers.
- Maximize Signal for Predictive Performance: Define the strategy for new signal sources. You will mathematically quantify the value of these signals and work with modeling teams to incorporate them into predictive models, directly improving bidding efficiency and ROAS.
- Define Ground Truth & Evaluation Frameworks: Solve the industry-wide challenge of validating identity and measurement. Design the objective functions and truth sets used to train our models and measure the incremental impact of our identity graph.
- 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.
Qualifications:
Required:
- Advanced degree (Master’s or Ph.D.) in Statistics, Mathematics, Physics, Economics, or Operations Research
- For M.S. holders: 10+ years of industry experience in applied science or data science roles
- For Ph.D. holders: 6+ years of industry experience in applied science or data science roles
- Deep understanding of the ads ecosystem
- Demonstrated expertise in at least one of the following areas:
- Measurement & Experimentation at Scale (with focus on lift and attribution)
- Identity Graph Creation & Resolution Methodology and Infrastructure
- Predictive Modeling with Signal Loss
- 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 and Income Replacement Programs
- 401k with Employer Match
- Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
- Family Planning Support
- Gender-Affirming Care
- Mental Health & Coaching Benefits
- Flexible Vacation & Paid Volunteer Time Off
- Generous Paid Parental Leave
#LI-Remote
In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.
During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors.
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.
Annual salary information is not provided for this position. Explore salary ranges for similar roles in our Salary Directory ›
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