• Location
    • Remote
  • Date Posted
  • May. 25, 2021
  • Function
  • HR
  • Sector
  • Talent

We’re on a mission to make work better for everyone, everywhere. We empower people to thrive at work, without creating more work for them.

Who we are

We’re an action management platform that makes it easy for organizations to improve their morale, engagement, and performance—every single week. At Humu, we know that all great things start small, which is why we give people the exact step-by-step support they need to reach big goals.

We’re looking for passionate collaborators who are excited about building a product that empowers people to improve themselves, and the teams around them.

What you’ll get to work on

Humu’s Nudge Engine® deploys thousands of customized nudges—small, personal steps—throughout organizations to empower every employee, manager, team, and leader as a change agent. Over time, our nudges grow increasingly aware of the timing, messaging, and motivational techniques that inspire individual employees towards action.

The details

  • As a member of our Data Science team, you will:
  • Partner with members of Humu’s Customer Success team to understand, scope and advise on client analytical requests
  • Conduct rigorous custom analyses and create deliverables for clients based on your findings
  • Help scale compelling analytical insights by building automated internal processes and/or product features
  • Learn from and collaborate with other Data Scientists

Qualifications:

  • Strong background in human behavior, statistics and data analysis
  • PhD, Masters, or equivalent expertise in a field that uses analytics to understand human behavior (e.g., Organizational Behavior, Social/Personality Psychology, Behavioral Economics, Industrial/Organizational Psychology)
  • 2-99 years of experience working with either people data or product usage data (e.g., survey data, HR data, psychological study data, human behavior data, or product interaction data)
  • Expert knowledge of advanced statistical techniques (e.g., regression, cluster analysis, latent profile analysis, hierarchical linear modeling, choice modeling, social network analysis, Bayesian methodologies, etc.)
  • Proficient in R or Python
  • Proficient in SQL
  • Knowledge of Git a plus
  • Ability to translate data into compelling insights for a non-technical audience
  • Strong cross-functional collaboration and communication skills
  • Ability to navigate ambiguity and solve problems in a fast-paced environment