Senior Applied Scientist, Product

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 Applied 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:

• 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.

Here’s what you’ll be working on:

• Work with other applied scientists on projects to evaluate the health of both internal and external components to make sure the Moloco system is running safely and efficiently. 
• Learn from your senior peers how to identify new areas to improve our infrastructure and machine learning components by understanding internal system changes, external changes, and data changes, and identify and suggest interesting/useful next steps for your projects.
• Complete task as part of larger projects to complete deep unbiased analyses. 
• Implement, and evaluate new algorithms and features in collaboration with senior Applied Scientists, Software Engineers and Machine Learning Engineers.
• Analyze massive, high-dimensional datasets from ad auctions and user interactions to uncover insights, define success metrics, and guide modeling and product decisions.
• Collaborate closely with product, engineering, and other scientists to iterate on experiments, define roadmaps, and translate business requirements into scientifically sound solutions.
• Improve the reliability, latency, and efficiency of online prediction and decision systems by applying rigorous experimentation, monitoring, and continual model refinement.

Basic Qualifications:

• Advanced degree in Computer Science, Mathematics or related field, or industry experience in optimization of market prices or ML systems
• At least 4 years of engineering or applied science experience
• Proficient verbal and written English communication skills, with the ability to contribute to the creation of presentations and reports
• Quick understanding of new information and the demonstrated ability to learn new technical skills across engineering, machine learning, and data science
• Track record of building positive relationships with collaborators and stakeholders and working effectively with cross-functional partners in a global company