We’re looking for a Business Intelligence Analyst to join our growing team!

About The Role:

We’re seeking a data-driven Business Intelligence Analyst to turn blockchain and product data into clear, actionable insights that drive growth, retention, and risk controls across our crypto-enabled iGaming products. You’ll own the end-to-end analytics stack for wallet funnels, wagering behavior, lifecycle marketing, and compliance—using SQL, dbt, Python, Amplitude, and Tableau as your primary tools.

Key Responsibilities:

— Design, build, and iterate on Tableau dashboards that surface core KPIs (GGR/NGR, ARPU, LTV, churn, deposit→wager conversion, fraud loss rate).

— Write production-grade SQL (CTEs, window functions, incremental models) to model clean datasets from ClickHouse and on-chain tables.

— Use Python (pandas, seaborn, scikit-learn, SciPy) for analysis, data quality checks, lightweight ETL/backfills, API integrations (e.g., blockchain providers), and automation.

— Work with on-chain data: parse EVM logs and token transfers (ERC-20/721), join labeled-address datasets, analyze exchange/bridge flows, gas/fee dynamics, and wallet clustering.

— Own crypto wallet analytics across the funnel (custodial vs. non-custodial, deposits/withdrawals, conversion to first deposit).

— Partner with Product, Marketing/CRM, Risk/Compliance, and Engineering to define event schemas and tracking plans; ensure data quality, lineage, and documentation.

— Design and analyze experiments (A/B and holdouts), cohorts, and attribution within iGaming and regional compliance constraints.

— Investigate anomalies (bonus abuse, bot usage, arbitrage, suspicious wallet rings) and recommend mitigations.

— Automate recurring reporting and alerting for KPI movements.

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Qualifications:

— Experience: Minimum 2 years in Business Intelligence or Data Analytics; prior exposure to crypto or iGaming strongly preferred.

— Ownership & Impact: Demonstrated ability to build robust analytics infrastructure and scalable self-serve data products.

— SQL: Advanced proficiency with complex joins, window functions, performance optimization, and dimensional data modeling.

— Tableau: Expert use of LOD expressions, parameters, actions, data modeling, extract vs. live strategies, and dashboard performance tuning.

— dbt: Hands-on experience with environments, sources/exposures, testing, documentation, and CI/CD integration.

— Python: Proficient in analytics and data engineering (e.g., pandas); capable of writing modular, maintainable code, integrating with APIs, and scheduling lightweight jobs.

— Crypto Domain: Practical understanding of crypto wallets and transaction flows, including custodial vs. non-custodial models and WalletConnect/MetaMask.

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Preferred Qualifications:

— Experience with dbt Cloud, data quality tooling (Great Expectations, Monte Carlo), and workflow orchestration (Airflow, Prefect).

— Demonstrated ability to perform on-chain analytics using platforms such as Dune, Flipside, Goldsky, or Nansen, or via self-indexed data; familiarity with contract ABIs and entity/address labeling.

— Hands-on experience with modern data warehouses and object storage, including ClickHouse, AWS, and Amazon S3.

— Working knowledge of data governance and privacy standards (e.g., GDPR), including data minimization and retention policies.

— Strong understanding of iGaming economics and KPIs: deposits, wagers, hold, GGR/NGR, RTP, bonus efficiency, responsible gaming metrics, and common fraud/AML patterns.

— Familiarity with product analytics platforms (Amplitude, Mixpanel, Google Analytics).