Part-time Data Quality Analyst

Owl Labs Inc.

Toronto

Remote

CAD 21,000 - 41,000

Part time

4 days ago
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Benefits offered by this job

Employee Referral Program

Job summary

Owl Labs Inc. is seeking a Data Quality Analyst to help ensure the integrity of insurance claims processing with open data sources and analytics. This is a remote, part-time position requiring at least 15 hours per week and up to 30 hours.

You will investigate data quality, document findings clearly, and collaborate with Owl’s AI platform while maintaining data security and confidentiality. A reliable internet connection is essential.

Qualifications

  • Previous experience in open-source content research.
  • Ability to work independently in a remote environment.
  • Strong written and verbal communication skills for documenting research findings effectively.
  • Very comfortable on the computer - ability to type quickly, utilize various search functions and keyboard shortcuts.
  • Analytical thinker with the ability to exercise creative problem-solving during investigations.
  • Ability to adapt quickly to evolving technologies and system processes.
  • Due to the remote nature of this role, secure & reliable internet connection is critical to be considered.

Responsibilities

  • Conduct investigations utilizing open data sources and in partnership with Owl’s AI.
  • Ensure findings are inputted logically, leveraging our internal platform to guide the process.
  • Analyze external claimant data for quality, completeness, and accuracy.
  • Efficiently utilize time and resources to deliver high-quality results that maximize value for the company.
  • Maintain the security and confidentiality of sensitive information.
  • Operate within company security and disclosure guidelines.

Skills

Open-source research
Written communication
Independent remote work
Analytical thinking
Problem solving
Typing speed
Secure internet access

Job description

We’re building applied AI systems for high‑stakes, real‑world decisions. Our platform ingests and reasons over large, messy data to surface evidence with hard constraints around fairness, auditability, and low bias.

The single gnarliest, most impact‑heavy place this problem shows up is in insurance claims, so that’s where we’re deployed today, running in production at some of the largest carriers in North America.

As a Data Quality Analyst, you will play a pivotal role in leveraging data to ensure the integrity and accuracy of insurance claims processing. Pulling from open data sources, you will support our clients in monitoring, detecting, and preventing potential illegitimate claims.

This is a remote, part-time role (15-30 hours/week).
Responsibilities & Scope

Conduct investigations utilizing open data sources and in partnership with Owl’s AI.

Ensure findings are inputted logically, leveraging our internal platform to guide the process.

Analyze external claimant data for quality, completeness, and accuracy.

Efficiently utilize time and resources to deliver high-quality results that maximize value for the company.

Maintain the security and confidentiality of sensitive information.

Operate within company security and disclosure guidelines.

Requirements
Must be available to work at least 15 hours/week.

Previous experience in open-source content research.

Ability to work independently in a remote environment.

Strong written and verbal communication skills for documenting research findings effectively.

Very comfortable on the computer - ability to type quickly, utilize various search functions and keyboard shortcuts.

Analytical thinker with the ability to exercise creative problem-solving during investigations.

Ability to adapt quickly to evolving technologies and system processes.

Due to the remote nature of this role, secure & reliable internet connection is critical to be considered.

Benefits
The compensation for this role is $20.00 per hour.

Bring your friends on board! Help grow our team of top performers and receive a cash bonus through our uncapped, generous Employee Referral Program.

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