Elliptic London, England, United Kingdom · Data
Jan 11, 2019Permanent
Description At Elliptic we believe cryptocurrency will play a huge role in the future of value transfer, and we care deeply about helping to build this future. In order for cryptocurrency to flourish, it's important to prevent criminal abuse of the technology. Elliptic is the global leader in detecting, preventing, and pursuing criminal activity in cryptocurrencies. Our clients include the world's leading cryptocurrency exchanges, financial institutions and government agencies. Our unique platform gives us an unparalleled understanding of cryptocurrency capital flows, using a combination of network science and machine learning to aggregate and interpret vast quantities of transaction data. We provide anti-money laundering (AML) compliance software and investigative services to the leading participants in the cryptocurrency ecosystem. Customers rely on us to analyse more than $150bn of their transactions every month, and include cryptocurrency businesses, major financial institutions, and federal government agencies. The company has offices in London, UK, New York, NY, and Arlington, VA. We are backed by Octopus Ventures, SignalFire, Paladin Capital, Santander InnoVentures, and Digital Currency Group. What's the role? Elliptic is looking for an ambitious, passionate data scientist who will have a key role in developing our cutting-edge blockchain analysis platforms. We leverage open source technologies but have also built our own high-performance, in-memory data pipeline and analytics engine. This is a full-time role in our London office. What you'll do: Work with engineers to turn pertinent analyses into production-ready algorithms for client facing products Collaborate with other data scientists and engineers to enhance and develop our data science toolkit Conduct independent research to uncover signs of illicit financial activity in cryptocurrencies and deanonymise bad actors Run experiments to evaluate new features and heuristics Requirements REQUIREMENTS 1+ years' relevant industry experience Solid understanding of basic statistics and machine learning Strong knowledge of data science tools and frameworks: python, pandas, scikit-learn Some experience in database technologies, and management of data and data pipelines A strong, quantitative degree (computer science, maths, physics,...) Passion for exploration, experimentation and building with large data sets Strong coding skills in at least one language Bonus points for: Knowledge of Scala or Java Good Software Engineering fundamentals (testing, code design) Experience with Graph Databases (e.g.: Neo4J) Experience with Cloud Computing Platforms (AWS / GCP) Knowledge of Spark, SparkML, Java Machine Learning Libraries (e.g.: SMILE) Knowledge of data analysis relevant to the blockchain - think network/graph theory Previous working experience in startups Experience relating to AML, fraud detection or forensics Appetite for discussions about economics, money, identity and privacy Interest in Bitcoin A quantitative PhD (computer science, maths, physics,...) Benefits Share options Private health insurance Work pension scheme Shiny laptop and multiple monitors Budget for training materials, events, and conferences Quarterly full day offsites Annual company 3 day offsite Coffee and beer!