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Staff Data Scientist - Remote

Posted 35 weeks ago
Data Analysis
Full Time
USA
$235,000 - $250,000/year

Overview

Zefr is the leading data company enabling responsible marketing in social media environments. Zefr’s solutions empower brands to understand content on scaled platforms such as YouTube, Meta, TikTok, and Snap. Through its patented AI technology, Zefr offers brands and agencies more accurate and transparent targeting and measurement solutions.

In Short

  • Hiring a Staff Data Scientist to build and use machine learning models.
  • Implement machine learning algorithms to analyze social media posts.
  • Work with state of the art models and large language models.
  • Collaborate in a learning environment.

Requirements

  • Bachelor's or Master's degree in Computer Science or related field with 7+ years of experience.
  • Experience with training classifiers, encoders, and generative models.
  • Fluency with Python and SQL, specifically Snowflake.
  • Experience with distributed systems and machine learning models.
  • Strong foundation in data structures, algorithms, and software design.
  • Strong communication skills.

Benefits

  • Flexible PTO.
  • Medical, dental, and vision insurance.
  • Company-paid life insurance.
  • Paid parental leave.
  • 401(k) with company match.
  • Professional development opportunities.
  • 14 paid holidays off.
  • In-office, hybrid, and fully-remote work options.
  • “Summer Fridays” (shorter work days on select Fridays).
  • In-office lunches and free food.
  • Optional in-person and virtual events.
Zefr logo

Zefr

Zefr is a leading data company focused on enabling responsible marketing within social media environments. With a strong emphasis on understanding content across major platforms like YouTube, Meta, TikTok, and Snap, Zefr leverages patented AI technology to provide brands and agencies with accurate and transparent targeting and measurement solutions. Headquartered in Los Angeles, California, Zefr operates globally, fostering a culture of innovation and collaboration in the fields of machine learning, computer vision, and natural language processing.

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