Data Scientist — Blockchain Intelligence
About Merkle Science
Merkle Science specializes in blockchain transaction monitoring and intelligence solutions, catering to various sectors like web3 companies, digital asset service providers, financial institutions, and government agencies. The company aims to ensure the safe and compliant growth of cryptocurrencies by detecting, investigating, and preventing illicit activities related to cryptocurrencies.
Merkle Science is headquartered in New York and also has presence in Singapore, Bangalore, and London. The team comprises professionals with diverse experience from notable organizations like Bank of America, Paypal, Luno, Thomson Reuters, and Amazon. The company has secured substantial funding from various investors.
Job Responsibilities:
- Develop and implement clustering and attribution heuristics to convert on-chain activity into reliable intelligence, working closely with attribution and clustering leads.
- Take charge of the entire data process, including extraction, cleaning, integration, and modeling of extensive on-chain datasets independently.
- Create and manage pipelines that facilitate the transition of heuristics from concept to production, encompassing tasks like backfills, incremental runs, and validation.
- Research and analyze specific cases like mixers, bridges, and exchange hot wallets, translating discoveries into systematic processes.
- Collaborate with investigative and product teams to establish accuracy benchmarks and align with ground truth standards.
- Quickly prototype solutions and refine successful techniques.
Qualifications:
- Possess over 4 years of experience in deploying data science or data engineering solutions.
- Proficient in Python and SQL with expertise in handling large datasets and addressing scalability challenges.
- Solid understanding of clustering, graph/network analysis, or entity resolution, with a focus on validating outcomes rigorously.
- Able to balance precision and coverage considerations effectively and explain chosen metrics convincingly.
- Self-motivated and capable of independently navigating through ambiguous scenarios to deliver desired outcomes.
Tech Stack:
- Platforms like Databricks, Kafka, Python, and TigerGraph form the core technology utilized for day-to-day operations.
- Additional technologies such as SQL for analysis, ClickHouse for aggregate queries, and Git/GitHub for version control are commonly integrated.
- Functions related to orchestration, scheduling, and cloud services within the GCP environment are also part of the ecosystem.
Working Environment:
The company emphasizes a small, high-trust team dynamic with significant autonomy and minimal red tape. The approach involves rapid prototyping, transparent measurement practices, and timely delivery.
Well Being, Compensation, and Benefits:
The well-being of employees is a top priority at Merkle Science, ensuring a healthy work-life balance through flexible schedules, learning programs, and mental health discussions. Competitive compensation packages, generous equity offerings, and numerous opportunities for career advancement underscore the company's commitment to recognizing and rewarding talent.
