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Gaming Data Analyst Jobs in Alberta (NOW HIRING)

Statistician Spotter

Calgary, AB

CA$15.45 - CA$19.44/hr

This role is perfect for individuals interested in sport analytics, officiating, coaching, or team operations. The Spotter contributes directly to the quality of live game data and plays a critical ...

... gaming skins, - competitive pay and performance-based bonuses, - flexible, remote work ... analyzing data and applying improvements, - collaborating with product and marketing teams ...

... gaming skins, - competitive pay and performance-based bonuses, - flexible, remote work ... analyzing data and applying improvements, - collaborating with product and marketing teams ...

... gaming skins, - competitive pay and performance-based bonuses, - flexible, remote work ... analyzing data and applying improvements, - collaborating with product and marketing teams ...

... gaming skins, - competitive pay and performance-based bonuses, - flexible, remote work ... analyzing data and applying improvements, - collaborating with product and marketing teams ...

... gaming skins, - competitive pay and performance-based bonuses, - flexible, remote work ... analyzing data and applying improvements, - collaborating with product and marketing teams ...

... gaming skins, - competitive pay and performance-based bonuses, - flexible, remote work ... analyzing data and applying improvements, - collaborating with product and marketing teams ...

... gaming skins, - competitive pay and performance-based bonuses, - flexible, remote work ... analyzing data and applying improvements, - collaborating with product and marketing teams ...

... gaming skins, - competitive pay and performance-based bonuses, - flexible, remote work ... analyzing data and applying improvements, - collaborating with product and marketing teams ...

... gaming skins, - competitive pay and performance-based bonuses, - flexible, remote work ... analyzing data and applying improvements, - collaborating with product and marketing teams ...

... gaming skins, - competitive pay and performance-based bonuses, - flexible, remote work ... analyzing data and applying improvements, - collaborating with product and marketing teams ...

... gaming skins, - competitive pay and performance-based bonuses, - flexible, remote work ... analyzing data and applying improvements, - collaborating with product and marketing teams ...

... gaming skins, - competitive pay and performance-based bonuses, - flexible, remote work ... analyzing data and applying improvements, - collaborating with product and marketing teams ...

... gaming skins, - competitive pay and performance-based bonuses, - flexible, remote work ... analyzing data and applying improvements, - collaborating with product and marketing teams ...

... gaming skins, - competitive pay and performance-based bonuses, - flexible, remote work ... analyzing data and applying improvements, - collaborating with product and marketing teams ...

... gaming skins, - competitive pay and performance-based bonuses, - flexible, remote work ... analyzing data and applying improvements, - collaborating with product and marketing teams ...

... gaming skins, - competitive pay and performance-based bonuses, - flexible, remote work ... analyzing data and applying improvements, - collaborating with product and marketing teams ...

... gaming skins, - competitive pay and performance-based bonuses, - flexible, remote work ... analyzing data and applying improvements, - collaborating with product and marketing teams ...

... gaming skins, - competitive pay and performance-based bonuses, - flexible, remote work ... analyzing data and applying improvements, - collaborating with product and marketing teams ...

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Gaming Data Analyst information

What does a gaming data analyst do?

A Gaming Data Analyst is responsible for collecting, analyzing, and interpreting data generated by players and game systems. They use statistical techniques and data visualization tools to identify trends, player behaviors, and opportunities for game improvements. Their insights help game developers optimize gameplay, enhance user experience, and increase player retention. Gaming Data Analysts often collaborate with designers, developers, and marketing teams to inform decisions based on data-driven evidence.

What are the key skills and qualifications needed to thrive as a gaming data analyst?

To thrive as a Gaming Data Analyst, you need strong analytical skills, statistical knowledge, and proficiency in data visualization, typically supported by a degree in mathematics, statistics, computer science, or a related field. Familiarity with data analysis tools such as SQL, Python, R, and visualization platforms like Tableau or Power BI is essential. Excellent communication, problem-solving abilities, and a passion for gaming help analysts interpret data insights and collaborate effectively with game development teams. These skills are crucial for transforming raw data into actionable strategies that enhance player engagement and drive business growth.

How does a gaming data analyst typically collaborate with game developers and designers?

Gaming Data Analysts work closely with game developers and designers by providing insights derived from player data, gameplay metrics, and user behavior. They often attend cross-functional meetings to discuss findings and recommend data-driven changes that could improve player engagement, retention, or monetization. This collaboration ensures that game features and updates are informed by actual player patterns, leading to more impactful and enjoyable gaming experiences. Effective communication skills and the ability to translate complex data into actionable recommendations are essential in this collaborative environment.

How much do gaming data analysts make?

Gaming data analysts typically earn between $50,000 and $90,000 annually, depending on experience, location, and company size. Entry-level roles may start lower, while experienced analysts with skills in data visualization and SQL can earn higher salaries.

How to become a gaming data analyst?

To become a gaming data analyst, you typically need a bachelor's degree in fields like data science, statistics, or computer science. Developing skills in data analysis tools such as SQL, Excel, and programming languages like Python or R, along with understanding gaming industry metrics, is essential. Gaining experience through internships or projects can also improve job prospects.

What job categories do people searching Gaming Data Analyst jobs in Alberta look for?

The top searched job categories for Gaming Data Analyst jobs in Alberta are:

Infographic showing various Gaming Data Analyst job openings in Alberta as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 14% Part Time, and 2% Contract. Highlights an 83% Physical, 5% Hybrid, and 12% Remote job distribution.

Senior Data Engineer - Oil & Gas

Data Elephant Inc

Calgary, AB

Contractor

Re-posted 11 days ago


Job description

We are looking for a Senior AI/ML Engineers to join our team, that sit at the intersection of software engineering, data engineering, and applied AI.



This role is ideal for someone who enjoys building end-to-end solutions - from data pipelines and backend systems to AI-powered applications - and wants to work on real-world industrial use cases that comes from an Engineering background, and has experience in Oil & Gas.


In this position, you'll contribute to a variety of impactful client projects, including:


  • Building AI-powered anomaly detection systems for operational and industrial data
  • Modernizing asset management workflows
  • Developing natural language interfaces for querying enterprise and operational data
  • Designing and implementing AI agents and copilots for business users
  • Creating scalable data pipelines and ML workflows in cloud environments
  • Enabling real-time and batch data processing for analytics and AI use cases
  • Working through complex and challenging data conditions, including incremental processing, late-arriving or changing records, complex business and engineering rules, and reconciliation of results across processing runs


The ideal candidate combines strong data engineering experience with an engineering or applied-science background. Direct experience industrial time-series data, scientific measurements, telemetry, financial reconciliation, or other datasets where accuracy, traceability, and incremental recalculation are critical.


Key Responsibilities


  • Design, build, and optimize pipelines for sensor and related operational data.
  • Develop complex transformation and calculation logic based on engineering requirements.
  • Implement robust incremental-processing patterns for high-volume and continuously changing datasets.
  • Design, build, and deploy end-to-end AI/ML solutions in production environments
  • Develop robust backend systems and APIs to support AI-driven applications
  • Build and maintain data pipelines and feature engineering workflows
  • Implement and operationalize machine learning models (training, deployment, monitoring)
  • Work with modern AI tooling (LLMs, agents, orchestration frameworks)
  • Collaborate with clients to translate business problems into technical solutions
  • Contribute to architecture decisions and best practices across projects
  • Mentor client team members and contribute to internal capability building
  • Work directly with engineering and operational SMEs to understand physical processes and translate their knowledge into technical requirements.
  • Make engineering calculations and data transformations explainable, traceable, testable, and auditable.
  • Document data lineage, calculation logic, assumptions, dependencies, and exception-handling rules.


Ideal Background

  • Senior-level experience designing and developing production data pipelines with Azure Databricks including strong experience with complex SQL, Python, Spark, or comparable data-processing technologies.
  • Demonstrated experience with incremental processing, change detection, reconciliation, and idempotent pipeline design.
  • Experience handling time-series, telemetry, sensor, operational, scientific, or industrial data.
  • Ability to work through ambiguous requirements with highly specialized SMEs.
  • Strong analytical and investigative skills, with the patience to work through detailed logic and difficult data-quality problems.
  • Degree or professional background in petroleum, reservoir, chemical, mechanical, geological, geophysical, or another relevant engineering or applied-science discipline is strongly preferred.
  • Experience in upstream oil and gas, thermal operations, SAGD, well surveillance, production engineering, or subsurface data would be a significant asset.
  • Hands-on experience with AI/ML workflows and model deployment.
  • Modern developer tooling (Cursor, AI-assisted development, Langraph, "vibe coding").



    This role presents an exciting opportunity to work on practical, high-impact AI use cases - not just prototypes, shape how AI is applied to client environments, and change the game on traditional processes and platforms.Come join a growing organization helping clients take a new, lean and value-driven approach to data and engineering!