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remoteroles

Data Scientist - Data Analytics and Infrastructure

Ample Insight Inc. ampleinsight.com Open · verified Oct 24, 2026
Remote Toronto Full-time Mid-level Data Analysis & BI

At a glance

Mid-level Data Analysis & BI role at Ample Insight Inc. Remote, Canada · full-time · no salary stated · we estimate CA$75,000–CA$101,994.

Estimated pay

Ample Insight Inc. has not published a salary for this role. The figure below is our estimate, not theirs.

CA$75,000 – CA$101,994
What the middle half of mid-level data analysis & BI roles in Toronto paid, among postings that did state a salary.
Worked out from 42 postings that stated pay, median CA$91,625. Last updated Oct 23, 2026.
RoleData Analysis & BI
SeniorityMid-level
LocationToronto
WorkplaceRemote
EmploymentFull-time
PostedSep 5, 2025 · 1y ago
Role brief

remoteroles summary, based on the employer's posting.

What you'll do

  • Design and keep production data systems running so analytics can scale reliably
  • Automate data workflows and make information accessible across teams
  • Work with large, complex datasets to produce insights that inform business decisions
  • Build analytics systems and maintain the pipelines that support them
  • Create data schemas and put analytics tracking plans into practice

What you bring

  • A bachelor’s degree or higher in computer science, data engineering or a related technical discipline
  • Hands-on experience building and supporting data pipelines and infrastructure in production
  • Strong SQL and large-scale data preparation skills, plus proficiency in Python
  • Knowledge of statistics, data modeling and performance tuning

Who this fits

This role suits a mid-level data scientist who enjoys combining data engineering, analytics and statistics to work with complex datasets. It is based in Toronto and listed as remote.

From the employer

You will join a world-class team of engineers and data scientists from Facebook, Uber, Amazon and Google. We are a fast growing consulting firm based in Toronto with clients ranging from leading startups building impactful technologies to Fortune 500 companies looking to scale their engineering and data capabilities.

We are looking for Data Scientists passionate about Data Analytics and Infrastructure, with strong foundations in data engineering, analytics, and statistics. You should enjoy working with large, complex datasets and developing efficient pipelines that enable scalable, reliable data analytics.

You’ll be responsible for designing and maintaining data infrastructure, automating workflows, and enabling data accessibility across teams. Your work will directly impact business decisions by delivering high-quality insights and building robust analytics systems. Strong problem-solving, communication, and collaboration skills are key for this role.

  • BS (or higher, e.g., MS, or PhD) in Computer Science, Data Engineering, or a related technical field

  • Experience building and maintaining data pipelines and infrastructure in production environments

  • Proficient in SQL and data wrangling at scale (e.g., Spark, Airflow, dbt, etc.)

  • Strong grasp of statistics, data modeling, and performance tuning

  • Skilled in Python (Pandas, Numpy, etc.) and data visualization tools (e.g., Tableau, Power BI)

  • Familiarity with cloud data platforms (e.g., AWS, GCP, Azure)

  • Ability to design data schemas and implement analytics tracking strategies

  • Analytical mindset with a focus on impact, efficiency, and scalability

We have competitive compensation.

Work on cool projects based on your interests and skills. We believe in accountability and NOT micro-management.

Opportunity

Data Analysis & BI work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Data Analysis & BIRemote

Find me work

By the team behind remoteroles.

Find me work
Opportunity

Data Analysis & BI work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Find me work

By the team behind remoteroles.