Job Title: Risk Data Analyst Location: San Jose, CA Here are a few must haves and additional info: Strong SQL proficiency Experience applying statistics and data science to tackle intricate business challenges Proficiency in AWS Quicksight and Tableau The position is hybrid, so candidates must be local to San Jose area. Potential to extend based on business need and performance.

Day shift: M-F Pacific time Multiple Zoom interviews (2-3) - SQL assessment during 1st interview Job Description: We are looking for a talented, enthusiastic and dedicated person to join the Risk Portfolio & Program Management team. The incumbent will be responsible for identifying and driving key initiatives to monitor credit and fraud risk of the company. You will leverage your python and SQL skills to pull and manipulate data, analyze clusters and relationships.

Professional Experience/Background to be successful in this role: Bachelor's degree in business analytics, data science, statistics, mathematics, engineering, other relevant degree, or equivalent practical experience Experience using statistics and data science to solve complex business problems Proficiency in using SQL and Excel for data analysis purposes Proficiency in data visualization and building dashboards using Tableau Experience working with large data sets Clear communication skills, being able to translate complex results to technical and non-technical business partners and executives Preferred Skills: Relevant industry experience in ecommerce, online payments, banking, risk management Demonstrated experience developing key performance indicators and how to measure success for either key initiatives or a team portfolio Proficiency in Python or R for more complex data analysis Experience with AWS Expected Outcomes in 6 to 12 months: Understand fraud and credit risk and develop approaches to mitigate loss and responsibly grow revenue. Monitor performance of strategies and portfolios Document and communicate results and escalate issues as necessary. Identify gaps/opportunities and drive actions.

Evaluate third party vendor data quality and identify new opportunities leveraging various data elements to improve customer experience without incremental risk exposure Craft dashboards to track Fraud and Credit related initiatives such as KPIs around funnel conversion and strategy/portfolio performance; summarize and present findings to senior management Work closely with Data and Product teams to ensure data quality are accurately and as design.