Betty2mo ago

Data Analyst | Betty CA

Bulgaria·Sofiasenior

Data AnalystData

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Quick Summary

Key Responsibilities

Own deep-dive analysis of player and commercial behavior — where value is created, where it leaks, and what we should do about it. Form and test hypotheses about why things happen,

Technical Tools

Data AnalystData

Betty is an innovative entertainment company pioneering at the intersection of real-money online casinos and casual mobile gaming.

We are honest - we value honesty in all aspects.
Bring the Olives - we offer premium customer experience.
Think Big - we believe in always striving for more.

Responsibilities

~1 min read

→Own deep-dive analysis of player and commercial behavior — where value is created, where it leaks, and what we should do about it.
→Form and test hypotheses about why things happen, and turn the answer into a recommendation — including how it affects our players.
→Work with large event-level data in Redshift to run deep-dives and ad-hoc investigations.
→Lead advanced analyses: cohort analysis, segmentation, LTV and retention modelling, funnel optimization, effectiveness measurement.
→Find opportunities and inefficiencies across player segments, games, providers, payment flows, and channels.
→Run ad-hoc analysis to support business initiatives, product launches, and marketing campaigns.
→Support experimentation and A/B testing: define success metrics, analyze results, and know when a result is real.
→Build and maintain the reporting the business runs on, from the tables underneath to the dashboards on top.
→Present findings and recommendations credibly to any audience, up to C-level.

3+ years in data analytics — ideally iGaming, gaming, fintech, or another high-volume consumer-transaction environment.
Advanced SQL, with Redshift or a comparable cloud data warehouse.
Hands-on Tableau, or a comparable BI tool.
Deep knowledge of commercial and behavioral KPIs: LTV, ARPU, retention, churn, cohort behavior, conversion funnels.
Experimentation and statistical reasoning, including an instinct for correlation vs. causation.
The ability to work with messy, incomplete, evolving data and still produce something reliable.
Clear communication — you can explain a complex analysis to someone who doesn't want the detail, and manage expectations honestly.
Being comfortable in a fast-paced environment.