Associate – Fraud Analytics

Bachelor’s Degree in Technology, Statistics, Business Analytics, related field (Master’s preferred), or comparable experience
3+ years of analytical experience in the consumer finance industry
3+ years of experience leveraging data tools such as SQL, R, Python
3+ years of experience conducting data analytics in a lending/banking organization
Ability to translate analysis results into clearly defined and implementable strategies/rules
Strong quantitative and problem-solving skills with key attention to detail
High level of inquisitiveness, initiative, and critical thinking
Proven ability to effectively communicate with all levels of staff and management
Prior experience in statistics and machine learning modeling techniques through coursework or professional experience
Proven ability to communicate findings clearly to both technical and non-technical audiences

Develop and implement fraud rules using analytical methods like segmentation, predictive models, hypothesis testing, etc.
Use visualization tools like looker to build dashboards and monitor key performance indicators
Use data to understand new ways of finding impactful insights from limited data sets and develop recommendations
Assist with data wrangling and automation of data pipelines for real time alerting and performance monitoring
Own and run key processes to reduce fraud losses
Analyze data, create models/strategies, and recommend solutions for the latest fraud trends
Work with stakeholders throughout the company to identify opportunities for leveraging company data and third-party vendor data to drive business solutions
Work with the team to measure impact and make updates to the model/strategies and services as needed
Communicate results, explain behavior of models/strategies, and set appropriate expectations with stakeholders
Strategize on building models and assist with deployments into production
Doing ad-hoc analysis and presenting results in a clear manner to Sr. Management