Role overview
CoinList is where the world’s best crypto projects build their communities and early adopters can invest in and trade top-tier digital assets. Our mission is to accelerate the advancement of blockchain technology, by finding the best emerging blockchain projects and helping them succeed. CoinList has become the global leader in new token issuance, helping blue chip projects like Solana, Filecoin, Celo, Dapper Labs, and others raise over $800 million and connect them with hundreds of thousands of new token holders. And we now support the full lifecycle of crypto investment, from token sales through token distribution, trading, lending, and crypto-specific services such as staking and access to decentralized-finance opportunities. CoinList users trade and store Bitcoin, Ether, and many other popular crypto assets through CoinList.co, CoinList Pro (our full-service exchange), and mobile apps, while also getting exclusive access to the best new tokens before they list on other exchanges.
Unlike other centralized crypto finance platforms, we're not here to just build a bank or a brokerage. We're building the platform for people who are passionate about moving crypto forward, and we’re just getting started. Come join us and propel the future of crypto!
Our team is growing fast, and we're looking for someone to help understand and present our data so we can build and grow more effectively.
What you'll work on
- Work with various stakeholders to understand fraud mitigation objectives, available data, and fraud patterns.
- Work with the data team to design and implement data pipelines for fraud detection models.
- Build data science and machine learning models to detect fraud. Present the model to stakeholders and drive decision making on the model selection.
- Work with the engineering team to deploy the model into production, in a stable and scalable environment.
- Create and manage dashboards to help people track important KPIs and metrics.
What we're looking for
- 3-5 years of experience as a data scientist or machine learning engineer
- Proficient in SQL and python (including pandas, numpy, scipy, etc.)
- Experience with fraud detection is a big plus. If not directly fraud, at least experience with developing models for anomaly (outlier) detection is a must. Examples: defect detection (manufacturing, operations), disease detection (genomics data science).