About Block Labs
Block Labs is a premier technology studio operating at the bleeding edge of Web3, Artificial Intelligence, and iGaming. We don't just ship features; we engineer high-scale, production-grade platforms that power the next generation of digital products.
We are a collective of senior engineers, product strategists, and builders who refuse to compromise on architecture. Whether we are designing autonomous multi-agent AI systems, building decentralized financial infrastructure, or architecting high-frequency iGaming platforms, our standard is excellence.
We move fast, but we build for the long term. If you are looking to work alongside a team that values deep technical expertise, thoughtful system design, and product ownership, Block Labs is where you belong.
About The Role
We’re looking for a data-obsessed BI Analyst to turn blockchain and product data into crisp 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. In the future we planning transition from Tableau to other BI tools alternatives like Metabase or Apache Superset or others.
Key Responsibilities
- Drive the business forward through proactive analytics - don't just fulfill dashboard requests; spot anomalies, frame the right question yourself, and bring actionable recommendations to Product / CRM / Risk before they have to ask.
- Build, maintain, and iterate dashboards surfacing 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.
- Build and maintain AI-agent workflows that automate recurring analytics - anomaly investigation, root-cause loops etc.
- Use Python (pandas, seaborn, sklearn, scipy) for analysis, data quality checks, lightweight ETL/backfills, API pulls (e.g., blockchain providers), and automation.
- Work with on-chain data: parse EVM logs, token transfers (ERC-20/721), join labeled address datasets, analyze exchange/bridge flows, gas/fee dynamics, and wallet clustering.
- 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, cohort analyses, and attribution within iGaming and regional compliance constraints.
- Investigate anomalies (bonus abuse, botting, arbitrage, suspicious wallet rings) and recommend mitigations.
- Automate recurring reporting and alerting for KPI movements.
What kind of culture can I expect?
Mature, mission-driven, and low-ego. We value clarity over noise, outcomes over theatrics, and pace without chaos. If you’re one of the smartest minds in your craft and want to build with other experts, you’ll feel at home here.
Must-haves
- 2+ years in BI or Data Analytics; crypto or iGaming exposure prefered.
- Ambitions about building great analytics infrastructure.
- Good SQL: complex joins, window functions, query optimization, and dimensional modeling.
- Solid AI-collaboration craft — prompt & context engineering, spec-driven task framing, and eval-driven iteration. Comfortable decomposing business questions into precise, agent-executable steps and designing the right tools for the agent to call.
- BI Versatility: Expert knowledge of Tableau (LODs, parameters, performance tuning) combined with a strong interest or experience in modern, open-source BI tools like Metabase or Apache Superset.
- Proficient Python for analytics & data engineering: pandas, modular scripts/notebooks, API integrations, scheduling small jobs, and writing maintainable code.
- Solid statistics and probability fundamentals for experimentation - hypothesis testing, sample size and power, confidence intervals, and the discipline to distinguish real signal from noise.
- Practical understanding of crypto wallets and transaction flows.
Nice-to-haves
- dbt, Great Expectations/Monte Carlo for data quality; orchestration with Airflow/Prefect.
- Built or contributed to production AI agents for analytics — ReAct loops, RAG over a knowledge base , MCP servers for data sources, multi-agent orchestration. Knows how to curate domain knowledge for agents so they stop hallucinating.
- Ability to produce on-chain analytics (Dune/Flipside/Goldsky/Nansen tables or self-indexed data; contract ABIs; entity labeling).
- Warehouse ecosystems knowledge Clickhouse, AWS, S3 buckets.
- Data governance & privacy (GDPR, data minimization, retention policies).
- Understanding of iGaming economics & KPIs: deposits, wagers, hold, GGR/NGR, RTP, bonus efficiency, RG metrics, and common fraud/AML patterns.
- Experience with product analytics services like Amplitude, Mixpanel, Google Analytics.
