Senior Data Scientist Ads Optimization Ml at Reddit

Location: US remote-friendly
Reddit is continuing to grow our teams with the best talent. This role is completely remote friendly and will continue to be after the pandemic. 
We are looking for a Senior level Machine Learning Data Scientist to build new ML products to improve ad performance and advertiser ROI. You will work closely with engineers and product managers from the Advertiser Optimization team to up-level the current Budget Pacing system, build ML-based auto-bidding products, as well as develop reinforcement learning models for dynamic creative optimization (Ad Level Optimization). This person is an industry technical leader in the online ads marketplace optimization domain with a solid technical background, strong business acumen, and excellent cross-functional stakeholders management skills. 
Responsibilities:

You will dive deep into the Budget Pacing system and help the team identify efficiency gaps and areas for improvement. You will research and develop ML-based PID controllers and auto-bidding products to improve advertisers’ performance.
Research, design, and develop contextual bandit models or similar reinforcement learning techniques for dynamic creative optimization (DCO) that can improve ad performance and bring more value to advertisers, especially for Shopping Ads. 
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 (experiment design and analysis, data deep dive), along with working on ETLs and data aggregations needed for training, testing and productionizing models. 
Serve as a thought-partner for product managers, engineers, leadership in shaping the monetization roadmap and strategy for Reddit by identifying opportunities through deep-dive analyses and/or modeling.

Required Qualifications:

Relevant experiences in ads marketplace.
Ph.D., M.S. or Bachelors degree in Statistics, Machine Learning, Operations Research, or other quantitative fields (If M.S. degree, a minimum of 1+ years of industry data science experience required and if Bachelor’s degree, a minimum of 2+ years of industry data science experience).
Proficiency in at least one of the areas: operations research, operations management, control theory, reinforcement learning, statistical modeling, and optimization.
Deep understanding of online experimentation and causal inference.
Strong analytical and communication skills.
Strong skills in programming (Python or R) and SQL.

Benefits:

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

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: $183,000 - $275,300
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