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Remote Insurance Data Analytics Jobs in Toronto, ON

London, ON | Hybrid/Remote | StarTech.com StarTech.com is continuing to grow our Data Analytics team and we are looking for a Data Analyst who is passionate about turning data into actionable ...

LiDAR Data Analyst (Co-op)

Concord, ON · On-site +1

CA$46K - CA$61K/yr

This role offers a unique opportunity to gain hands-on experience with advanced mapping, remote ... Analyze point cloud and image data using internal software tools and workflows. * Perform quality ...

With a fully remote workplace, we provide our team the flexibility they need to thrive both at home ... The Data & Analytics pod produces the insights, data assets and context that inform our strategies ...

Fully Remote (Canada, EST time zone) Compensation: Salary + Bonus + Health Benefits About Veem Veem ... Shape the future of B2B payments -- Data Engineer, BI & Reporting (Analytics Engineer / BI Engineer ...

Analyze large data sets and identify trends and insights to inform business decisions; communicate ... TD requires employees to reside in the country where the role is located, irrespective of remote ...

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Remote Insurance Data Analytics information

What is remote insurance data analytics?

Remote insurance data analytics is the practice of analyzing insurance-related data, such as claims, risk assessments, and customer information, from a location outside of a traditional office setting. Professionals in this field use statistical methods, data mining, and machine learning tools to identify patterns, detect fraud, and help insurance companies make data-driven decisions. This remote role often requires proficiency in data analysis tools like SQL, Python, or R, and a strong understanding of insurance industry concepts. Remote insurance data analysts collaborate with teams virtually to provide insights and support business strategies, making it a flexible career option.

What are the key skills and qualifications needed to thrive as a remote insurance data analytics professional?

To excel in Remote Insurance Data Analytics, you need strong analytical skills, a background in statistics or mathematics, and typically a degree in data science, actuarial science, or a related field. Familiarity with data analysis tools like SQL, Python, R, and specialized insurance analytics platforms such as SAS or Tableau, as well as relevant certifications, is highly valuable. Attention to detail, problem-solving abilities, and effective communication set candidates apart in this role. These skills are crucial for transforming complex insurance data into actionable insights that drive informed business decisions and risk assessments.

How do remote insurance data analytics professionals typically collaborate with cross-functional teams to drive business insights?

Remote Insurance Data Analytics professionals often work closely with underwriters, actuaries, claims managers, and IT teams to gather data requirements, interpret findings, and implement data-driven solutions. Collaboration usually happens through virtual meetings, collaborative dashboards, and project management tools to ensure clear communication and alignment on objectives. This cross-functional approach helps identify trends, optimize risk assessments, and support strategic decision-making within the organization. Building strong relationships with team members across departments is key to successfully translating analytical results into actionable business strategies.

What is the difference between Remote Insurance Data Analytics vs Remote Insurance Underwriter?

AspectRemote Insurance Data AnalyticsRemote Insurance Underwriter
Required CredentialsBachelor's in Data Science, Statistics, or related field; often certifications in data analysis or analyticsBachelor's in Business, Finance, or related; often requires insurance licensing or certifications
Work EnvironmentPrimarily data analysis, modeling, and reporting; often collaborative with IT and actuarial teamsAssessing risks, reviewing applications, making underwriting decisions; involves communication with agents and clients
Employer & Industry UsageUsed across insurance companies, reinsurers, and brokers for data-driven decision makingUsed by insurance carriers to evaluate and approve policies

Remote Insurance Data Analytics focuses on analyzing insurance data to inform business decisions, while Remote Insurance Underwriters evaluate individual insurance applications to determine coverage. Both roles are essential in the insurance industry but differ in daily tasks and required skills.

What are popular job titles related to Remote Insurance Data Analytics jobs in Toronto, ON?

For Remote Insurance Data Analytics jobs in Toronto, ON, the most frequently searched job titles are:

What job categories do people searching Remote Insurance Data Analytics jobs in Toronto, ON look for?

The top searched job categories for Remote Insurance Data Analytics jobs in Toronto, ON are:

Infographic showing various Remote Insurance Data Analytics job openings in Toronto, ON as of September 2026, with employment types broken down into 1% As Needed, 74% Full Time, 19% Part Time, and 6% Contract. Highlights an 88% Physical, 1% Hybrid, and 11% Remote job distribution.

Manager, Data Analytics - Canada

Toronto, ON • Remote

CA$300/day

Full-time

Medical, Dental, Vision, Life

Re-posted 15 days ago


Job description

About the Role:

Zenni is experiencing rapid growth in the affordable eyewear space, and data is at the core of our success. We are seeking a Manager, Data Analytics with a strong technical background and deep business domain expertise to partner closely with our Engagement Marketing team.

In this leadership role, you will bridge the gap between complex data architecture and strategic marketing initiatives. You will be responsible for translating large datasets into clear, actionable insights, empowering our cross-functional teams to make confident, informed decisions. By building robust data solutions and fostering strong collaboration across departments, you will directly impact our operational efficiency and drive revenue growth. If you are a collaborative leader who excels at leveraging data to solve real-world business challenges, this could be the next move for you!  This is a remote role overseeing a team of 2 and reporting to the Sr. Director of Data Engineering.

Responsibilities:
  • Champion data literacy: Provide ongoing training and support to the Engagement Marketing team, ensuring complex data concepts are seamlessly communicated and understood.
  • Drive cross-functional alignment: Act as the strategic bridge between the Data and Engagement Marketing teams, streamlining communication to boost operational efficiency and collaboration.
  • Power marketing platforms: Integrate enriched, highly trusted data with key business platforms (e.g.,Google, Tik Tok, Meta) to optimize ad delivery and AI performance.
  • Ensure data integrity: Own the lifecycle of data feeds, encompassing validation, monitoring, testing, and proactive alerting, to guarantee uncompromising data quality and reliability.
  • Define success metrics: Partner with functional teams to establish a shared, accurate understanding of the core metrics that drive organizational performance.
  • Shape the data roadmap: Lead the strategic planning for the data team, ensuring technical initiatives directly align with Zenni's overarching growth objectives.
  • Innovate continuously: Stay at the forefront of modern data engineering technologies and industry trends to evolve our strategy and keep our technical capabilities competitive.
Basic Qualifications:
  • Bachelor's degree in Computer Science, Machine Learning, Engineering, or a related technical discipline.
  • 8+ years of dedicated experience in the data area, coupled with at least 3 years navigating the fast-paced e-commerce landscape.
  • Deep business domain knowledge across key marketing functions, including but not limited to Performance Marketing, Lifecycle, and Brand Marketing.
  • Hands-on experience implementing marketing measurement methodologies, including Last-Touch, MTA, incrementality testing, MMM, and CVR measurement frameworks.
  • Extensive experience designing data architecture, performing complex data modeling, and building scalable ETL/ELT pipelines for centralized data warehouses.
  • Advanced fluency in SQL and Python, with the ability to dive deeply into a modern tech stack as a hands-on contributor.
  • Demonstrated success leading projects from start to finish, spanning requirement gathering, cross-functional stakeholder communication, architecture design, implementation, and QA.
  • Proactive leadership and cross-functional communication skills, with a proven ability to drive business impact.
Preferred Qualifications:
  • Hands-on expertise working within Databricks environments.
  • Proven track record of guiding and mentoring high-velocity data teams in a fast-paced setting.
  • Demonstrated success managing complex data integrations, advanced reporting, and platform optimization across diverse marketing channels.
  • An enthusiastic, proactive approach to tackling new technical challenges and driving continuous improvement.
Canada Perks & Benefits:
  • Annual bonus program
  • 100% employer-paid medical, dental, and vision (dependent coverage capped at $300/month)
  • Life, AD&D, and disability coverage (with optional add-ons)
  • Company-matched RRSP contributions up to 4%
  • Comprehensive wellbeing programs (mental, physical, emotional support)
  • Lifestyle Spending Account (wellbeing + learning)
  • Work-from-home stipend (for eligible roles)
  • Generous Flexible Time Off in addition to our Week of Zen - the time between Christmas and New Year's to relax and recuperate
  • Fully Paid Parental Leave - 16 weeks for birthing and non-birthing parents
  • Family forming & fertility support and services through Maven
  • Annual Zenni Gift Card - to use towards our products

Compensation

In addition to other forms of compensation like perks and benefits, the estimated range for this role is CAD 163,000 - 185,000. The final offer will be determined based on permissible, non-discriminatory factors such as skill set, experience, geographical location, market conditions, and other organizational needs. The Company reserves the right to change, modify, or revisit the salary range for various reasons including business needs.