Data Scientist II

Indeed•Remote,

1d•$125,000 - $259,000•Remote

About The Position

Indeed is the world's largest marketplace for jobs, with a unique dataset spanning jobs, resumes, applications, and outcomes. As a Senior Data Scientist on the Utility team in Marketplace Efficiency, you will extend Indeed's marketplace optimization across the core and partner sites. You will partner with senior scientists to bring ranking and utility optimization to Indeed's core sites as well as our international and partner sites across Japan marketplace, Glassdoor, and new surfaces such as Career Scout. You will own initiatives that find opportunities to improve ranking and marketplace outcomes on these surfaces. You will design experiments, analyses, and models that tune the shared ranking utility for each surface. You will define the metrics and guardrails that show when a change helps jobseekers and employers. You will also build reusable tools and methods so that optimization work transfers across surfaces with less effort. You will work with product, engineering, and science teams across Indeed, Glassdoor, and our Japan organizations to inform surface roadmaps. Your work will turn one optimization approach into results on many surfaces.

Requirements

Requires a Bachelor’s degree in Computer Science, Mathematics, Statistics, or related field and a minimum of 5 years of related experience; or a Master’s degree with a minimum of 3 years of experience; or a PhD without experience
Expertise in A/B testing and experimentation is required
Solid foundation in data science methods and technologies.
Able to influence technical direction and contribute to long-term planning.
Able to work effectively with other teams and mentor colleagues.
Experience with ranking, recommendation, or matching systems, including offline and online evaluation
Experience with optimization methods, such as constrained or multi-objective optimization, applied to ranking or marketplace problems

Nice To Haves

Loves thought-provoking assignments and is eager to learn.

Responsibilities

Oversee data-driven initiatives that uncover opportunities to improve product performance and business outcomes.
Design and execute advanced analyses, experiments, and machine learning models to address complex product and business questions.
Partner with product and engineering teams to define metrics, track performance, and inform both short- and long-term product strategies.
Mentor and guide other data scientists, fostering best practices in methodology, modeling, and analytical thinking.
Collaborate across teams to influence decisions with clear, compelling insights and visualizations tailored to diverse audiences.
Contribute to the development of tools, techniques, and processes that enhance the efficiency and impact of the data science team.
Serve as a recognized technical resource in the organization, helping solve high-impact problems and advising on analytic approaches.