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Data Scientist

Data scientist for Organizational Network Data

Humanyze helps companies measure and improve organizational health. Born out of the MIT Media Lab, Humanyze uncovers the hidden patterns of digital and face-to-face communication to uncover areas of improvement in engagement, productivity, and adaptability. Humanyze is committed to helping teams work better together and has the data and science to prove it. Humanyze’s cutting edge platform delivers advanced insights and is used by Fortune 500 companies to answer specific business questions around collaboration, space planning, workload, performance measurement, and regulatory and compliance risk.

This position is based in Menlo Park, CA or Boston, MA.

The Team:
We come from diverse backgrounds, enjoy solving challenging problems in a fast-paced, agile environment, and are passionate about our company's mission to make work better.

Role description
This role will be leading the development of a core functionality of the Humanyze Organizational Health Platform, Humanyze Intelligence. The datasets we work with are collected from multiple sources, including email, calendar, calls, and IMs as well as physical sensors. With a rapidly growing user base, we are in need of a Data Scientist who would be responsible for creating scalable intelligence to extract predictive models metrics from large, multi-source, multi-dimensional datasets.

In this role, a Data Scientist would be expected to:
  • Design, prototype, and implement machine learning models for predictive analysis, anomaly detection, and time series analysis for multi-dimensional social network data collected in real-world organizations.
  • Research and implement new/custom algorithms and methodology
  • Leading the effort in scaling the analysis for large organizations.
  • Work closely with product, engineering, and marketing team to architect and develop operational models that run at scale
  • Provide technical leadership by proposing models, guiding junior scientist and reviewing experiments and models

Required skills:
  • MS or PhD degree in a quantitative discipline: Computer Science, Network Science, Statistics, Operations Research, Informatics, or related disciplines.
  • Or 3+ years of professional experience in the application of machine learning, social network analysis, or data science 
  • 3+ years of experience in at least one programming language such as Python/R/Java/C++
  • A strong proficiency in analyzing large data sets
  • The ability to connect quantitative metrics to real-world interpretations and analysis
  • Excellent communication and collaborative skill
  • Must work well in multi-disciplinary teams

Desired skills
  • 5+ years of relevant work experience in relevant industry/academia
  • Experience with distributed data systems such as Hadoop and related technologies (Spark, Presto, Pig, Hive, etc.).
  • Experience with organizational behavior data

We Offer:
  • Competitive salary and bonus
  • Flexible work environment
  • Generous medical, dental, vision and long-term disability insurance
  • SIMPLE IRA matching
  • 20 vacation days, 4 personal days plus paid holidays
  • Fully paid parental leave