Overview

About AssistIQ:

At AssistIQ we are dedicated to providing healthcare providers with an easy way to generate accurate data and insights on their supply usage to improve their value of care, reduce waste and carbon footprint. We’re building an AI-driven software platform that provides seamless tracking, real-time visibility and actionable insights to healthcare systems, while improving efficiency for multiple teams.

AssistIQ is looking team members who share our values:

  • Caring & Integrity: Making a positive difference in society and doing the right thing, honestly and transparently
  • Listening & Learning: Obsessing about our customers and how to solve their pain points
  • Openness: Challenging the status quo & embracing change, respecting new ideas and perspectives
  • Collaboration & Empowerment: Maintaining a growth mindset and displaying grit, passion and perseverance to achieve our goals, individually and as a a team

About the Role:

We are looking for a Lead Data Scientist with a demonstrated track record of leading data teams and building new data products using existing and novel data sets. They must be proficient at leading discovery and feedback sessions with a wide range of external stakeholders to understand customer data needs and uncover data opportunities. They must be comfortable working closely with internal product teams to understand the capabilities of the platform and ensure the right data sets are being built.The ideal candidate is adept at using large data sets to find opportunities for product and process optimization and using models to test the effectiveness of different courses of action; they must be inquisitive to investigate, test and confirm relationships between seemingly unrelated data sets. They must have experience managing product roadmaps for data and insights. They must have strong experience using a variety of data mining/data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms and creating/running simulations. The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes.

What You Will Do:

  • Work with external stakeholders across a wide spectrum of seniority and job functions to identify opportunities for leveraging data to build new data products.
  • Lead the data science team that is responsible for building innovative new data products
  • Understand, mine and analyze data from company databases to develop a data product roadmap for the company.
  • Ensure the data product roadmap that is complementary with the existing product roadmaps so the right data sources are being built across the platform.
  • Assess the effectiveness and accuracy of new data sources and data gathering techniques.
  • Develop custom data models and algorithms to apply to data sets.
  • Use predictive modeling to increase and optimize customer efficiency, customer insights and other business outcomes.
  • Develop company A/B testing framework and test model quality.
  • Coordinate with different functional teams to implement models and monitor outcomes.
  • Develop processes and tools to monitor and analyze model performance and data accuracy.

What You Bring

We’re looking for someone with 5-7 years of experience manipulating data sets and building statistical models, has a Master’s or PHD in Statistics, Mathematics, Computer Science or another quantitative field, and is familiar with multiple software tools, coding languages and databases. You bring:

  • Strong problem solving skills with an emphasis on product development.
  • Experience managing and leading data teams.
  • Experience leading requirements and discovery sessions for data products.
  • Experience in either the medical, supply chain or retail industries is an asset.
  • Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights from large data sets.
  • Experience working with and creating data architectures.
  • Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
  • Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
  • Excellent written and verbal communication skills for coordinating across teams.
  • A drive to learn and master new technologies and techniques.
  • A curiosity to discover new relationships between novel datasets.