We are looking for a manager to be a part of the Ads Data Science team and
lead a small group of machine learning and analytics data scientists. You will
work closely with engineering managers, engineers and product owners from our
Ads team to optimize ads delivery and auction systems. In addition to strong
ML skills, this person has a solid business acumen and understands what is
important to advertisers.
- You will start off with leading a team of 4-5 data scientists with some specializing in Machine Learning and others in analytics. The expectation is to scale the team to ~10 in 2023.
- You will build optimization algorithms that improve ad yields and efficiencies. Our optimization models were hugely successful in the last 12 months and as a result we are increasing our investment in this area.
- Along with building ML models, you will be a key strategic player in defining the roadmap for the ML efforts for the entire Ads Org. Your roadmap will not only achieve immediate business goals, but also dictate our long term strategy for optimization and marketplace efforts.
- Manage and nurture a team of talented Data Scientists and have a keen interest in shaping their careers.
- Some of the models we developed over the last year are CPC (cost per click), CPI (cost per install), Generalized pCVR (probability of conversion rate), ALO (Ad Level Optimization) and User Lookalikes. You will not only work on improving existing optimization models, but also develop new models from scratch for a variety of upcoming product launches.
- Build and improve Machine Learning algorithms that match ads to the most relevant users. Some of the algorithms/techniques used are Logistic Regression, Gradient Boosted Decision Trees, Random Forests, Hyperparameter tuning, Thompson Sampling, Monte Carlo simulations, Semantic Embedding models etc.
- Design and build a platform for rapid model iteration and feature engineering at scale. Some of our optimization models are iterated on and deployed in production every 2 weeks!
- Be involved in all phases of modeling such as ideation, offline modeling, online implementation, experimentation, deploy and post-launch monitoring/measurements.
- This role will have a lot of overlap with other Machine Learning Engineer roles, but will differ in a couple of areas. First is that you will work mainly on offline modeling and rely on engineers to productionize your models. Secondly, you will have a keen interest in the collection and quality of underlying data, along with working on ETLs and data aggregations.
- Serve as a thought-partner for product managers, engineering managers and leadership in influencing the monetization roadmap and strategy for Reddit by identifying opportunities through deep-dive analyses and/or modeling.
- Work closely with our sales and marketing partners to ensure that ads are set up in a way that amplifies the benefits of your optimization models.
- Master’s or PhD degree in a quantitative major (e.g., mathematics, statistics, economics, finance, computer science).
- Proficiency in Machine Learning
- 2 years of Prior experience working as a Tech Lead or a Data Science Manager. Willing to consider candidates without prior management experience.
- 5+ years of experience in quantitative/modeling roles, preferably for a consumer-facing service/app
- Proficiency with statistical analysis and programming languages (Python, SQL)
- Understanding of experimentation and causal inference analyses
- Experience building Ads optimization models is preferred but not required
- Comprehensive Health benefits
- 401k Matching
- Workspace benefits for your home office
- Personal & Professional development funds
- Family Planning Support
- Flexible Vacation & Reddit Global Days Off
- 4+ months paid Parental Leave
- Paid Volunteer time off
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
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: $198,200 - $297,300