Data Science Intern

Visier Solutions IncVancouver, BC
$5,500

About The Position

Visier is the global leader in Workforce Intelligence that powers every people decision. We bring Workforce AI to life for HR departments through our award-winning, agentic AI technology by surfacing the insights leaders need to plan, decide, and act with confidence in the moments that matter most. As the market leader in people analytics, workforce planning, organizational design, and manager effectiveness solutions, we fuel smarter decision-making for organizations across the globe. Our mission is to help businesses lead with insight at scale as they continuously transform. Founded in 2010 by the pioneers of business intelligence, we have over 85,000 customers in 75 countries—including enterprises like BASF, Panasonic, Domino’s Pizza, Experian, Amgen, eBay, and Ford Motor Company. Our co-op/intern experience is unique and designed to prepare you for professional success. Our ultimate goal is to give you the mentorship, training and work experience you need to start your career successfully! As part of Visiers R&D organization, our data science team is responsible for the development of advanced numerical algorithms and statistical techniques that generate business insights from human resource data. Mentored by an experienced Data Scientist you will collaborate on projects that match both your interests and Visier business needs. This could be software engineering focused (e.g. enhancing our machine learning pipelines or prototyping of automated insight generation), or research focused (e.g. unveiling compelling insights into the workforce from our unique multi-million employee cross-customers data set).

Requirements

  • Strong understanding of statistics and how to apply scientific methods to data using algorithms
  • Coding skills in Scala, Python or other relevant languages
  • Attention to detail and big picture thinking
  • Currently pursuing your Masters or PhD

Nice To Haves

  • Hypothesis testing
  • Machine learning techniques
  • Scientific analysis and knowledge generation

Responsibilities

  • Modelling the problem at hand, such that it directly solves underlying business problems
  • Brainstorming to identify the correct data required to solve business problems
  • Performing statistical analysis on data to build statistical/machine learning models
  • Identifying the right metrics to measure the success of the models and projects
  • Communicating and presenting your work to stakeholders across the organisation
  • Conducting independently research, in order to gain domain knowledge and learn cutting-edge techniques

Benefits

  • Mentorship
  • Training
  • Work experience
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