Director, Data Analytics at Olive AI

Remote
Olive AI

Director, Data Analytics

  • REMOTE
  • Analytics
  • United States
  • Full time

Description

Olive is healthcare’s first intelligent digital workforce and has been successfully deployed at numerous healthcare systems across the country. Olive helps streamline and automate the most high-volume, repetitive tasks so healthcare professionals can concentrate on their patients and solving healthcare’s most challenging problems. Olive’s promise to her customers is that she finds out where she can make an impact, onboards quickly, shows up to work everyday, does her job extremely well, and gets smarter over time.

Omega is Olive’s digital workforce operations center dedicated to ensuring that Olive keeps her promise, by providing support, analysis, communications, and continual improvements to all live customer bots.

The Director of Analytics at Olive is part of Omega’s rapidly growing Omega Analysis team. With Olive being deployed across the country, the Analytics Director will play a key role in developing the Olive data universe (the oliverse). We are seeking for this leader to establish a data analytics and management framework and build and grow a team that will help us accomplish several missions:

  1. helping to identify new work and deliver new insights to our customers through data modeling, statistics, deep learning, ML, and other mechanisms.
  2. developing customer performance analytics, both reflecting the performance of the bot and technology itself, and the business impact that Olive is having.

Work cross-functionally with other Olive leaders to accomplish the data mission. The ideal candidate is inquisitive, creative, self-driven and flexible with the ability to work within a dynamic high-growth startup environment.

Responsibilities (to include but not limited to):

  • Architect data environment and structure that supports scalability of data management and analysis
  • Work with sales team and customer-facing teams to define what data must be collected and the process for collecting data
  • Define data ingestion process and tools including data normalization, quality, etc.
  • Define strategy for tracking customer performance metrics including business metrics and technical performance metrics
  • Define customer success metrics by function and determine metric tracking strategy and customer-facing reporting
  • Build analytics team including hiring in key skill sets to manage and analyze data
  • Use complex data sources to blend and join data to deliver efficient and quality dashboards to live customers
  • Leverage advanced visualization techniques to extract analytic insights to help customers make informed decisions
  • Establish processes to ensure data quality and accuracy in both analysis and reporting
  • Drive business decisions by providing quantitative and qualitative data analysis and reporting of patterns, insights, and trends to internal and external stakeholders
  • Produce actionable reports that show KPI’s, identify areas of improvement into current operations, and display root cause analysis of problems
  • Use analytics and metrics to improve processes and provide data-driven forecasts for new business initiatives
  • Ensure that our business and technical teams can make decisions based on sound data insights
  • Provide reporting solutions and respond to ad-hoc report requests across multiple divisions
  • Utilize business intelligence tools to detect trends in technology issues and partner with the Omega engineering team to implement solutions

Requirements:

  • Bachelor’s degree in Mathematics, Economics, Computer Science, Statistics, or equivalent professional experience
  • Masters degree in one of the above or related fields preferred but not required
  • 7-10 years of professional experience in data architecture, data strategy, customer data analysis and value delivery, data management and manipulation, report writing, and/or database design
  • Experience building, growing and leading a group of technical resources including data scientists, data engineers and data analysts.
  • Strong working knowledge of analytics and data technologies including data storage, data management, data cleaning/wrangling and data analysis tools. (AWS Stack based)
  • Experience building data visualizations using tools like Tableau or similar
  • Ability to direct groups on how to analyze large data sets and collect insights in a fast-paced, agile environment
  • Experience with predictive analysis and statistical methods and exposure to deep learning and machine learning algorithms

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