We are looking for a Data Science Manager to lead the Ads Marketplace analytics team. You will partner closely with cross functional team leaders such as GPMs, Engineering Managers and other leaders in utilizing data to drive decision making.  In addition to strong analytical skills, you will have a keen business acumen and the big picture thinking that can guide our Ads Marketplace strategy in a data driven manner.

How You’ll Have Impact:

Advertising is Reddit’s primary business model 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 that drive action. This large number of self-governed communities have highly-engaged users who are in an unduplicated mindset of consuming relevant information. This has created the opportunity for Reddit to build a massive and highly differentiated ads business.

We spent the past few years building the foundations of a modern ad serving system, building features to help brand and performance advertisers find their audiences on Reddit and get high ROI on their ad spend. We’re now ready to build differentiated products on top of those foundations, utilizing data to drive the product decisions for both short term and long term bets. 

As a data science leader, you’ll be a key player in ensuring we make the right product decisions based on data insights and help define the culture that is driven through metrics and KPIs. Your work will not only impact millions of users and thousands of advertisers but also act as a data foundation for our rapidly growing ads business.

What You’ll Learn:

• Your team will partner closely with our Ads Product and Engineering team, which is the core driver of revenue for the company.  Your team will play a key role in developing Ads product strategy and experiments. You’ll play with petabytes of data full of user and advertiser interactions to develop a deeper understanding of Reddit’s ads ecosystem. 
• In addition, your team will work side by side with a world-class organization of Engineering, Machine Learning, Search, Data Science, Data Warehouse, and Analytics practitioners who work together to create a variety of capabilities for Reddit to be more successful in its decision-making and product creation. In this process, you will be exposed to a variety of new techniques in experimentation, statistical frameworks, machine learning, deep learning, and causal inference.

What You’ll Do:

• Analyze conversations and behaviors across Reddit's over 10,000 interest-based communities, and convert them into insights and product recommendations.
• Understand Reddit advertising and help the company improve Ads Revenue while simultaneously improving ROAS (Return on Ads Spend) for advertisers and ads quality for users.
• Conduct product/feature analyses, opportunity sizing, experimentation (A/B testing) and build dashboards/visualizations to assess product health.
• Organize data by designing table schemas, data pipelines, aggregations, alerts and general data infrastructure for the Ads Organization.
• Collaborate with various cross-functional stakeholders, including Product Managers, Engineers, Designers, UX Researchers, Data Engineers and Data Warehouse Engineers to lead projects related to organizing and analyzing data.
• Be an integral part of the Data Org, leveraging and contributing to the vibrant knowledge base, shared across a community of world-class data experts.

Who You Might Be:

• 5+ years of experience in data analytics or related quantitative role
• 2+ years of experience in the digital advertising space
• 2+ years of experience managing a team of 5 or more Data Scientists.
• Demonstrated ability to influence and guide product strategy with data
• Demonstrated ability to take ambiguous problems and solve them in a structured, hypothesis-driven, data-supported way
• Desire to mentor other data scientists and share best practices to elevate the data science practice at Reddit
• Strong ability to communicate and discuss complex topics with technical & non-technical audiences
• Proficiency with relational database (e.g., SQL) and statistical analysis/programming languages (e.g., R / Python)
• Proficiency with dashboarding tools (e.g. Mode Analytics, Tableau, Looker)
• Good understanding of Machine Learning techniques and platforms.