Data Scientist, Analytics

As a Data Scientist, you will have end-to-end ownership of generating insights, developing custom models and building critical analytics products. In collaboration with a highly skilled team of engineers, data scientists, and blockchain analysts, your goal will be to uncover valuable and defensible information that can be used to detect, prevent, and mitigate cryptocurrency fraud and financial crime.

The impact you will have here:

• Perform exploratory data analysis to uncover insights hidden in very large datasets and build compelling data-driven stories to support critical blockchain reports for industry leaders and global policy makers.
• Lead the implementation of new advanced analytics products that allow our customers to explore and uncover hidden insights through complex blockchain data such as assessing the risk of DeFi services, stablecoins, global regulations and other crypto-trends.
• Use your high-level business acumen to collaborate with our go-to-market team and work directly with our customers to understand their challenges and pain points in order to creatively translate them into impactful models and products.
• Work closely with financial crime and threat analysts to identify suspicious activities, identify complex trends and generate impactful insights.
• Collaborate with engineers and research scientists to design algorithms to analyze complex data structures inherent to cryptocurrencies and blockchains. This will involve working with distributed ledger technologies, cryptographic protocols, and transactional data to uncover suspicious activities.
• You will collaborate closely with engineers, data scientists, and threats analysts to align on project goals, methodologies, and deliverables. You will communicate your findings and insights effectively to both technical and non-technical stakeholders.
• Develop your skills through exceptional training as well as frequent coaching and mentoring from colleagues
• Establish best practices and statistical rigor around data-driven decision-making

What we’re looking for:

• Your academic background is in a quantitative field such as Computer Science, Statistics, Engineering, Economics or Physics. Advanced degree preferred.
• You have 5+ years of experience working in an analytical role.
• You have a strong knowledge of relational databases, (e.g. SQL)
• You think about data in terms of statistical distributions and have a big enough analytics toolbox to know how to find patterns in data and identify targets for performance
• You have experience exploring complex datasets to identify hidden insights and generate compelling stories
• You have customer facing experience and you enjoy sitting with the customers to understand their challenges.
• You have proven experience with at least one programming language (Python preferred) and are comfortable developing code in a team environment (e.g. git, notebooks, testing).
• You have a high tolerance for ambiguity. You find a way through. You anticipate. You connect and synthesize.
• You are delivery-oriented, able to lead and execute in a face-paced environment.
• You have excellent verbal and written communication skills and experience in influencing decisions with information.

About the Team:

• The team operates with a high level of collaboration and interdependence, fostering an inclusive culture where connections extend beyond work. We value diverse personalities and seek someone who is both results-driven and sociable, with strong communication, leadership, and teamwork skills, along with a positive, solutions-oriented mindset.
• As a globally distributed team, members may observe different timezones. However, most of the team will overlap between the hours of 7am-12pm PST for meetings and collaboration.
• All team members, regardless of location must have at least 4 hour overlap with PST business hours.
• The team is involved in 2 different on-calls
  • Analytics on-call: only requires focus on working time (average of < 1 hour a day every month)
  • Data Science on-call: full week on-call to ensure Data Science pipelines are running smoothly (average of 1-2 hours a day every 3 months)

Learn about TRM Speed in this position:

• Deliver a last minute impactful project for a key customer
• Build complex products effectively with tight timeframes (1-2 sprints for MVP)
• Work on several projects in parallel with different priorities and stakeholders