Data Scientist, Fraud Operations
Dapper Labs is at an inflection point in our journey and it might be the perfect time for you to join us. Less than 6 months ago we launched NBA Top Shot on the new Flow blockchain and it is already on track to be the fastest-growing marketplace in history. Over $200 million in sales in the past 30 days and counting – we need to scale our systems to handle the demand!
We're looking for engineering-minded data scientists – to build out our fraud operations team. You'll join a small team that's scaling rapidly and build sustainable foundations for the future.
Our data pipeline currently include Segment and Tableau. Most of our backend systems are in Go, frontends in React. We use vanilla postgres as well as Kafka event-driven architecture in NBA Top Shot.
We believe in an open digital future: one where people own the assets they pay for and have full transparency into the software they're using. We believe users should have the choice to leave apps without leaving the underlying network, and that the users and developers that constitute a network should benefit directly from the value they're helping create. Crypto, or blockchain, is the technology that enables this future. Blockchains are public computers that anyone can access, everyone can trust, and no-one can block or take down. Currencies and collectibles are only scratching the surface of what's possible.
Titles or years of experience don't matter to us – impact, authenticity, and values alignment do. We are now a remote-first team and open to hiring anywhere in the world.
About the role:
- Work cross-functionally to analyze large amounts of behavioural and transaction data to uncover fraudulent behaviour and activity
- Create predictive models to understand user-level fraud risk
- Consistently consume and produce massive amounts of data while optimizing for speed, accuracy, and quality
- Research and develop how advanced data science techniques and machine learning can enable and empower our fraud detection capabilities
- Innovate our data methods to create a single coherent platform with sources of truth that serve many stakeholders including the Dapper product team and our finance department
Bonus points if you have the following:
- You have previous experience working in fraud detection and prevention, with an understanding of the impact that has on other areas in the company where business and product decisions are made
- You are capable of applying your skills across a variety of use cases; inflexible specialists need not apply
- You have a bachelor's degree in a highly quantitate field (Computer Science, Machine Learning, Statistics, Mathematics), and a master's degree preferred
- You have 5+ years working experience in data science and or machine learning. Strong knowledge of SQL and python programming and graph databases
- You are naturally curious and passionate about fraud prevention: if something seems off, you want to investigate what's going on and solve the true problem
- You are capable of tackling very loosely defined problems and thrive when given autonomy in your day to day decisions
More about Dapper Labs:
Dapper Labs is the world's first blockchain entertainment company. We are the creators of industry-leading experiences including CryptoKitties and NBA Top Shot, as well as Dapper Wallet, the simplest way to manage your assets and use the blockchain. We are also the original developers behind Flow, a new decentralized blockchain designed from the ground up for scalability and ease of use.
Our mission at Dapper Labs is to make the world a more open, empowering, and enjoyable place through consumer adoption of decentralized technologies. We have raised over $350M from leading VCs including Fred Wilson (USV) and Chris Dixon as well as Venrock, Samsung, Google Ventures, Coatue, NBA players, and global artists, among others. Dapper Labs partners include the NBA and NBPA, the NFL-PA, Ubisoft, Warner Music, Turner, Dr. Seuss, Genies, and the UFC, as well as 100+ others.
Visit our website to learn even more about Dapper Labs, including information about benefits and perks.