Senior Data Analyst - Live Games & Insights

Big Viking Games

Toronto

On-site

CAD 100,000 - 120,000

Full time

14 days+

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Benefits offered by this job

Retirement plan

Benefits package

Wellness spending account

Generous time off

Job summary

Big Viking Games in Toronto is seeking a Senior Data Analyst to support our live games, including YoWorld and FishWorld. This is a hands-on analytics role for someone who loves digging into player behavior, building dashboards that tell a clear story, and turning raw data into decisions that improve product, monetization, live operations, and player experience.

You will partner closely with leadership, product, production, live operations, finance, and engineering to analyze what is happening,

Qualifications

3+ years of experience in data analytics, product analytics, business intelligence, data science, or a related analytical role.
Strong SQL skills with the ability to work across complex, multi-source data systems.
Experience analyzing large datasets and turning analysis into real product or business decisions.
Hands-on experience with data visualization tools such as Tableau, Power BI, Looker, Sigma, Metabase, or similar platforms.
Comfort with Python, R, or similar scripting languages for data transformation, analysis, automation, or modeling.
Strong understanding of metrics, cohorts, funnels, segmentation, retention, engagement, monetization, and behavioral analysis.

Responsibilities

Analyze player behavior, retention, engagement, monetization, economy health, content performance, and live operations performance across YoWorld and FishWorld.
Conduct quantitative analysis and financial modeling to evaluate feature opportunities, content plans, monetization risks, and strategic product decisions.
Build, maintain, and improve dashboards that translate complex data into clear, actionable insights for stakeholders across the studio.
Write, maintain, and validate complex SQL workflows to extract, transform, and analyze large-scale player and business datasets.
Partner with product, production, live operations, and engineering teams to define telemetry, instrumentation, and data collection requirements.
Investigate behavioral patterns, session habits, player lifecycle trends, wallet dynamics, purchase behavior, content engagement, and churn signals.
Support live operations planning by identifying what content, events, offers, and engagement loops are working, where they are underperforming, and what should be tested next.
Help define KPIs, reporting standards, metric definitions, and repeatable analytics processes.
Present findings clearly and confidently to leadership and cross-functional teams.
Turn ambiguous product and business questions into structured analysis, clear recommendations, and decision-ready narratives.
Use AI tools thoughtfully to accelerate analysis, summarize findings, improve workflows, and reduce repetitive reporting work.
Help improve data quality, reporting accuracy, and trust in the company’s analytics systems.