Summary

Become a Krakenite and build the future of crypto!

Proof Of Work

Employer: Payward Operations LLC (dba Kraken)

Position: Data Scientist I

Job Location:

Salary Range:

$116,700 to $164,000

The Opportunity:

Duties:

1. Partner with financial fraud, product, engineering, and other relevant stakeholders to identify, prioritize, and answer the most important questions where analytics, statistical and ML modeling will have a material impact on mitigating Financial Fraud.
2. Drive cross functional analytic projects from beginning to end: build relationships with
3. partner fraud teams, frame and structure questions, collect and analyze data, summarize and present key insights in support of decision making to mitigate fraud.
4. Work with engineers to evangelize data best practices and implement analytics solutions.
5. Develop, train, and deploy ML models serving predictions and automating fraud reduction
6. processes.
7. Collaborate with fraud leaders, subject matter experts, and decision makers to develop success criteria and optimize new products, features, policies, and models.
8. Communicate key results with self-serve tools (dashboards, analytics tools) for leadership and product management.
9. Develop payment anomaly detection, and data modeling tools to monitor key performance indicators to improve the efficiency of payment gateways.
10. Design experiments for product teams to test hypothesis and help with idea generation and refinement.
11. Build key datasets and data pipeline automation using SQL/Python/Airflow/ETL frameworks.
12. Telecommuting / work from home is permitted.

Skills You Should HODL

Must have experience with:

1. Building and deploying machine learning models to detect fraudulent activities
2. Advanced quantitative and data analysis, including estimation methods, time series analysis, and machine learning techniques
3. Data querying languages such as SQL, scripting languages such as Python, or
4. statistical/mathematical software such as R
5. Performing in-depth research projects, examining real-world data with
6. mathematical methods
7. Cloud-computing tools and platforms such as AWS or GCP; Data visualization tools such as
8. tableau, Qlik, or data studio
9. Working with large datasets, including tick data
10. Identifying and implementing infrastructure improvements to minimize overall latency and maximizing performance with packages such as Pandas or Pyspark
11. Building databases and creating ETL pipelines for large, complex data sets with Airflow.

Minimum education and experience required:

1. Bachelor’s degree or the equivalent in Computer Science, Data Science, Statistics or a related field
2. 3 years of experience in the crypto currency industry or related.

Employer will accept any amount of experience with the required skills.

Skills

• AWS
• Machine Learning
• Python
• SQL