Data Scientist (Remote)

This role is San Francisco based but can also be remote.

We are looking for a data scientist who is innovative, highly-motivated, and proactive. For this role, you will be part of a team that builds cutting-edge trading products in the cryptocurrency industry. You will be responsible for transforming data and generating actionable insights into our customer behavior and measuring the performance of our trading engine. You will collaborate and lead projects with product management, engineering, marketing, and growth teams. You will transform data from complex systems, generate performance metrics, and share the results with stakeholders at all levels of the company.Great benefits, amazing perks, remote work and travel opportunities, stock incentives, beautiful HQ office, and a flexible PTO policy make Kraken a great place to work. If you value having a seat at the table and want to make a big impact on guiding the direction of marketing and growth at one of the top crypto exchanges in the world, this role is for you.

Requirements

• A degree in Statistics, Computer Science, Physical Sciences, Economics, Math or a related technical field.
• 5+ years industry experience in data science or analytics
• A consistent track record of performing data analysis using Python, R, and/or SQL
• Experience using statistics and predictive analytics to solve complex business problems.
• The versatility and willingness to learn new technologies on the job.
• The ability to clearly communicate complex results to technical and non-technical audiences.
• Familiarity with other data tools such as Hive, Vertica, Tableau & Ruby is a plus

Responsibilities

• Partner with Kraken’s engineering, marketing, product, and finance teams to identify, prioritize, and answer the most important questions where analytics and modeling will have a material impact.
• Drive cross functional analytic projects from beginning to end: build relationships with partner teams, frame and structure questions, collect and analyze data, summarize and present key insights in support of decision making.
• Work with engineers to evangelize data best practices and implement analytics solutions.
• Collaborate with business leaders, subject matter experts, and decision makers to develop success criteria and optimize new products, features, policies, and models.
• Communicate key results with self-serve tools (dashboards, analytics tools) for leadership and product management.
• Develop anomaly detection, and data modelling tools to monitor key performance indicators to improve the efficiency of the products.
• Design experiments for product teams to test hypothesis and help with idea generation and refinement.
• Build key datasets and data pipelines using Python/ETL frameworks.