Senior Applied Scientist, Product

Description

The company is an AI-native performance advertising business with two products: an ads platform for mobile app marketers and a retail media platform for retailers and marketplaces. Both run on the same in-house AI system.

You will join the Product Analytics Data Science team, which works with R&D on the core ads product. The role focuses on improving performance through a close understanding of supply, demand, bidding and machine learning, and on turning data into scientific recommendations.

The team has a large, complex system to examine, and the work is at a scale few companies offer.

Responsibilities

• Run deep-dive analyses of large datasets using queries and scripts, pull real signal from noise, and recommend how to improve the ML and bidding system for customers.
• Build metric frameworks that show campaign health, and work out cause-and-effect links between the drivers.
• Track changes across the ads system and diagnose problems using input and output metrics for each component.
• Work with other applied scientists to check the health of internal and external components so the system runs safely and efficiently.
• Learn from senior peers how to spot infrastructure and ML improvements by looking at internal changes, external changes and data changes, then propose next steps for your projects.
• Take on tasks within larger projects that call for unbiased analysis.
• Build and test new algorithms and features with senior applied scientists, software engineers and ML engineers.
• Study high-dimensional data from ad auctions and user activity to define success metrics and guide modeling and product choices.
• Work with product, engineering and other scientists to run experiments, shape roadmaps and turn business needs into sound scientific solutions.
• Improve the reliability, latency and efficiency of online prediction and decision systems through rigorous experiments, monitoring and ongoing model refinement.

Requirements

• An advanced degree in computer science, mathematics or a related field, or industry experience optimizing market prices or ML systems.
• At least 4 years of experience in engineering or applied science.
• Strong spoken and written English, with the ability to help write presentations and reports.
• You pick up new information quickly and learn new technical skills across engineering, machine learning and data science.
• A record of building good working relationships with collaborators and stakeholders and of working well with cross-functional partners in a global company.

Conditions

U.S.-based employees get medical, dental and vision insurance, a 401(k) with company match, short-term and long-term disability cover, basic life insurance, and well-being benefits. They also receive up to 12 scheduled paid holidays a year, one Thrive Day off per quarter, and Flexible Time Off (FTO) for all employees.

Pay is set by work location, grouped into three regions. Region A (Menlo Park Office, New York Office, SF Bay Area, New York Metro Area): $188,000 - $235,000 USD. Region B (Seattle Office, Seattle, Los Angeles/Orange County, San Diego, Austin, Boston, Washington DC Metro Area, Miami): $169,200 - $211,500 USD. Region C (all other U.S. locations): $159,800 - $199,750 USD.

The successful candidate may be eligible for a bonus and equity awards, based on performance and the terms of the applicable plans.

Benefits differ by country, employment type and eligibility. A recruiter can explain the options in your region.

The company is an equal opportunity employer.

Benefits

• Medical, dental and vision insurance, a 401(k) with company match, disability cover and basic life insurance for U.S.-based employees.
• Up to 12 scheduled paid holidays a year and one Thrive Day off per quarter for U.S.-based employees.
• Flexible Time Off for all employees.
• Possible bonus and equity awards tied to performance.