Senior Data Scientist - CertiK

Born from groundbreaking research at Columbia University and Yale University, CertiK is a leading Web3 security company focused on securing blockchain protocols, smart contracts, and decentralized applications through cutting-edge security research, formal verification, and AI-powered technology. Founded in 2017 and headquartered in New York City, CertiK provides end-to-end security solutions including smart contract audits, penetration testing, on-chain monitoring, incident response, and compliance services for some of the largest projects in the digital asset ecosystem.

Today, CertiK supports thousands of enterprise clients and Web3 projects globally, with a distributed international team spanning North America, Asia, and Europe. The company is backed by leading investors including Coatue, Goldman Sachs, Insight Partners, and Sequoia Capital, and has been recognized by organizations such as the World Economic Forum and CB Insights for its contributions to blockchain security innovation.

About the Role

The primary responsibility of this role is to build/maintain ETL pipelines & process large datasets from APIs/databases/third-party platforms to enable real-time team analytics and automate data preprocessing (cleaning/normalization/validation) for client accounts using rule-based logic/statistical checks to ensure data quality & prepare analysis-ready datasets for modeling/reporting.

Analyze large-scale blockchain/transactional/social-media datasets to identify patterns/trends/anomalies/risk indicators.

Develop/apply machine learning models (graph-based algorithms & NLP techniques) for threat detection/behavioral analysis/monitoring.

Perform feature engineering/model training/testing/validation to ensure accuracy/robustness/interpretability.

Design/implement scalable data pipelines/ETL processes & CI/CD workflows for ingestion/preprocessing/aggregating blockchain & social media data.

Create dashboards/visualizations to deliver actionable insights & provide data-driven guidance for strategic planning.

Collaborate with engineering/product/business teams to translate analytical requirements into scalable data-science solutions.