Careers at Merkle Science

Our tech stack You don't need to have used all of these, but here's what you'd be working with day to day: Databricks — our lakehouse and processing backbone. Large-scale on-chain datasets are transformed and modeled here via Spark and SQL; most heuristics run as Databricks jobs against billions of transactions. Kafka — real-time ingestion of on-chain and transaction data. New blocks and events stream in continuously, so a lot of our work is designed to run incrementally rather than as one-off batch jobs. Python — the primary language for everything from exploratory analysis to production heuristics and pipeline code. TigerGraph — our graph database, where addresses, transactions, and entities live as a network. Clustering, traversals, and relationship queries (who funds whom, consolidation paths, entity linkage) happen here. Supporting cast you'll likely touch: SQL everywhere — for ad-hoc analysis, validation, and defining ground-truth datasets. Columnar / analytical stores (e.g., ClickHouse) for fast aggregate queries over large tables. Orchestration & scheduling for backfills and recurring pipeline runs. Git / GitHub for version control and code review — we expect pipelines and heuristics to be reviewed like any other code. GCP as our cloud environment. How we work Small, high-trust team. You'll have a lot of ownership and very little bureaucracy. We prototype fast, measure honestly, and ship. ❤️ Well Being, Compensation and Benefits We care about your well-being. Along with excellent health insurance, we offer flexible time off, learning & development initiatives and hours that are designed to provide work/life balance. We regularly host team-building sessions and encourage discussions around mental health. We reward talent and believe in acknowledging people for their contributions. We offer industry-leading compensation, along with generous equity. As a rapidly growing business, there are endless opportunities to grow your career with Merkle Science.

Working at Merkle Science