Data Scientist II, Product Analytics

Moloco • Redwood City, CA

2h

About The Position

About Moloco:
Moloco builds some of the most powerful AI advertising solutions in the world. Our name—short for "machine learning company"—reflects our core mission: democratizing access to the advanced AI that has historically been reserved for tech giants. Led by machine learning pioneers who built some of the most successful ad systems at Google, including YouTube's monetization engine and key search advertising technologies, we're transforming how businesses grow and compete in the digital economy.
Built with AI from day one, Moloco’s planet-scale machine learning platform powers a suite of solutions for advertising growth and monetization. Moloco Ads is an AI-powered platform that delivers real business outcomes for mobile app marketers through performance-based user acquisition. Moloco Commerce Media and Streaming Monetization solutions enable retailers, marketplaces, and streaming platforms to build revenue-generating ad businesses that balance user experience and advertiser performance.
Moloco is headquartered in Silicon Valley, with offices in Seattle, New York, San Francisco, Seoul, Beijing, Singapore, Bangalore, Gurgaon, Tokyo, Shanghai, London, Tel Aviv, and Berlin.
Moloco is a truly rewarding place to work and in an exciting period of growth, which you could be a part of. Join us today and apply now!
The impact you'll be contributing to Moloco:
Product Analytics Data Science (PDS) is the data science team that works closely with the R&D team on our core Ads product. As a Senior Data Scientist, you will drive performance improvement in our product through a deep understanding of the ads ecosystem (supply, demand, bidding, ML) and customer needs, and provide the data driven insight and scientific solutions.
Here’s what you’ll be working on:
Our team is responsible for:

Requirements

• Distinctive problem-solving skills, ability to articulate product questions, pulling data from large datasets and using statistics to arrive at a recommendation; ability to manage multiple projects at the same time.
• Proven ability to own complex projects end-to-end, even when you have to get creative: you do more than completing delegated tasks and always pay attention to detail to translate analysis results into business recommendations.
• Provide strategic thought partnership to cross-functional teams, leveraging data-driven insights to influence and guide product decisions, roadmap prioritization, and overall business strategy.
• Excellent verbal and written communication skills, with ability to present information and analysis results effectively.
• Statistics: strong knowledge and experience in experimental design, hypothesis testing, and various statistical analysis techniques such as regression or linear models.
• Programming: experience with Python, R or other scripting language, and database language (e.g. SQL) or data manipulation (e.g. Pandas, Dplyr).
• Ability to build positive relationships within the DS team and with Product Management, Engineering stakeholders ;work effectively with cross-functional partners in a global company.
• 3+ years of work experience (industry or postgraduate) in data science related fields or an advanced degree such as Master’s or PhD in a quantitative discipline with 4+ years of experience.
• Bachelor’s, Master’s and/or PhD in a quantitative discipline (e.g. Statistics, Operations Research, Bioinformatics, Economics, Computational Biology, Computer Science, Mathematics, Physics, Electrical Engineering, Industrial Engineering).

Responsibilities

• Conducting deep-dive analysis to influence R&D decisions and strategies: analyzing large datasets with queries and scripts, extracting valuable signals out of noise, and producing actionable insights into how we could improve Moloco’s complex ML and bidding system to drive outcomes for customers.
• Building the right metrics to measure campaign health: improving campaign performance monitoring by establishing the right metric framework, and understanding cause-and-effect relationships across drivers
• Evaluating ads system health: understanding changes and drivers of our complex systems, and diagnosing issues through a set of input/output metrics of each component.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 501-1,000 employees