Senior Data Analyst, Live Games

Big Viking Games•Toronto, ON

4d•CA$100,000 - CA$120,000•Hybrid

About The Position

Big Viking Games is seeking a Senior Data Analyst to support their live games, YoWorld and FishWorld. This is a hands-on role focused on analyzing player behavior, building insightful dashboards, and translating data into actionable decisions to improve product, monetization, live operations, and player experience. The analyst will collaborate with leadership, product, production, live operations, finance, and engineering teams to understand game performance and influence strategic decisions. The ideal candidate is comfortable in a fast-paced live-service environment, can structure complex data, and communicate insights effectively to diverse stakeholders. This is a hybrid role based in Toronto, requiring three days per week in the office.

Requirements

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.
Ability to build dashboards and reports that are clear, useful, and action-oriented.
Strong communication skills, with the ability to explain complex analysis in plain business language.
Ability to work independently, manage priorities, and bring structure to ambiguous problems.
Strong attention to detail and a high bar for data accuracy, consistency, and reliability.
Bachelor’s degree in Data Science, Statistics, Mathematics, Economics, Computer Science, Business Analytics, or equivalent practical experience.

Nice To Haves

Experience with Snowflake or similar modern cloud data platforms.
Experience in gaming, live-service products, social games, casual games, free-to-play games, virtual worlds, or digital products.
Experience with game economies, virtual currencies, pricing, bundles, offers, content performance, and player lifecycle analysis.
Experience with A/B testing, experimentation, statistical analysis, forecasting, or predictive modeling.
Experience supporting product managers, live operations teams, designers, finance teams, or executive stakeholders.
Experience with data modeling, dbt, analytics engineering, ETL/ELT workflows, or data quality processes.
Experience using AI tools such as ChatGPT, Claude, Gemini, or similar platforms to improve analytics workflows, reporting, research, and insight generation.
A genuine interest in games, player behavior, social products, and long-running online communities.

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.