Leverdemo 882mo ago

Data Scientist

United States·San FranciscoCo-opmid

Data ScienceData ScientistDataData & AI

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Overview

________This is an example!________ PLEASE READ: these jobs are testing jobs of Lever's testing environment - please do not apply for this job.

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Data ScienceData ScientistDataData & AI

________This is an example!________

PLEASE READ: these jobs are testing jobs of Lever's testing environment - please do not apply for this job.

Lever was founded ten years ago to tackle the most strategic challenge that companies face: how to recruit and hire top talent. We’re building the next generation of hiring software that companies like Netflix, Yelp, Cirque du Soleil, Shopify, and Spotify rely on to grow their teams. We've rethought the talent acquisition paradigm and are the innovation leaders in our space and looking for the right people to join us as we scale. We’re extraordinarily proud of the company we’ve built so far (not to mention humbled to be recognized as the #1 place to work in San Francisco, as well as a top workplace in the entire United States). Our people are Lever’s biggest competitive advantage and we’ll continue investing in our “Leveroos” and people-first culture.

Lever is hiring a Data Scientist to bring our data to life by uncovering insights and turning it into a tool through models and forecasts. The ideal candidate has worked successfully in technology organizations as a data scientist or similar role and has strong theoretical and practical skills.

Develop statistical analysis and models and apply them to solving real problems

Work with our product development team to guide product decisions through data-based recommendations

Define and report on metrics and KPIs

Automate analysis and data pipelines while ensuring our data infrastructure is set up for scale

Experience as a data scientist or equivalent

Experience with a variety of data manipulation tools and languages (SQL, R, Python)

A history of delivering and reporting on impact

Outstanding communication skills

A background in statistics and/or mathematics is preferred