Senior Decision Scientist, Risk Operations

About Kraken
As one of the largest and most trusted digital asset platforms globally, we are empowering people to experience the life-changing potential of crypto. Trusted by over 8 million consumer and pro traders, institutions, and authorities worldwide - our unique combination of products, services, and global expertise is helping tip the scales towards mass crypto adoption. But we’re only just getting started. We want to be pioneers in crypto and add value to the everyday lives of billions. Now is not the time to sit on the sidelines. Join us to bring crypto to the world.

About the role
As a Decision Scientist in Risk Operations, you will analyse data related to our clients and their transactions to determine which signals are indicative of a wide range of fraudulent and risky activities, including Payment Fraud, Scams, Account Takeover, Account Abuse, First Party Fraud, Phishing and other threats to the trust and safety of Kraken and our clients. Using the results of this data analysis, you will drive the development, deployment and monitoring of models that control transactions and other risky activity on Kraken.com and our mobile apps.
In addition to working with currently available data, you will also identify and recommend additional data and data sources that enhance the quality of decisions. You will work with the Risk Product Team and Operations to drive integration of this data into Kraken Risk Systems. You will apply innovative, entrepreneurial curiosity with technical knowledge, adept problem-solving skills, client insights and operational insights to develop best in class decision capability to protect clients and stakeholders from abuse across multiple different products and services. On this team, you're a resourceful, strategic team-player with a passion for protecting the reputation of our brand.
●Model Development: Develop, deploy and monitor models that drive fraud related decisions●Champion/Challenger testing: Validate data and model performance against output from existing models and rules.●R&D: Test new data, calculations and data sources for improved risk decisions.●Platform Optimization: Work with Risk Product Management to optimize decision platforms and related systems.●Operations Optimization: Work with Client Engagement Team to determine the best scale outcomes and actions driven by data, rules and model output.●Business Intelligence & Communication: Devising and build Business Intelligence insights intodata, model and operations performance. Produce and deliver summaries of performance, issuesand gaps to wide range of audiences, including Executives, Product Management, Operations and Compliance.
Requirements●Degree in Math, Statistics or Operations Research (advanced degree preferred but relevant work experience may suffice)●Proven track record using advanced quantitative and statistical methods and tools to drive high volume complex decisions at scale.●Experience in financial services and payments, preferably in quantitative risk analytics with evolving FinTech or similar environments.●Experience with and working knowledge of SQL, SAS, R, Mathlab, Python and Machine Learningtools and techniques.●Ability to parse and analyze data from large structured and unstructured data sets●Experience with BI platforms used to monitor and communicate data, model, rule, operations and business results to a diverse audience.●Experience working with Product Management and Engineering, preferably in an Agile environment●Advanced logical, analytical and critical thinking skills●Strong attention to detail with a drive to solve problems, investigate issues, and creatively optimize quantitative, operational and business results.
Nice to Have●Advanced Degree in quantitative discipline●Working knowledge of Crypto and related products and service●Proven high quality communication and persuasive skills●Experience managing teams responsible for analysis & modelling



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As an equal opportunity employer we don’t tolerate discrimination or harassment of any kind. Whether that’s based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status or any other protected characteristic as outlined by federal, state or local laws. 
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