Finance Data & Risk Analytics Specialist

LendingUSA, LLC.; California (MO); On-site; USD 93,184 - 100,000; Full time

Job summary

LendingUSA, LLC. is seeking a data analyst to design, implement, deliver and analyze enterprise data to produce actionable analytical insights and models for finance and risk teams.

You will conduct profitability and risk analyses to support business growth, product pricing and risk management; deploy new strategies into decision engines and monitor data quality and auditing capabilities. Collaborate with Technology to transform raw data into usable formats and respond to data requests.

Qualifications

• Master's degree in Finance or related field.
• Coursework in Applied Data Analysis, Finance, Quantitative Business Analysis, Advanced Statistical Tools, Modern Portfolio Theory, Financial Modeling, and Financial Risk Management.

Responsibilities

• Design, implement, deliver, and analyze enterprise data to produce actionable analytical insights and models for finance and risk teams.
• Conduct profitability and risk analyses in support of business growth, product/pricing enhancement and risk management.
• Support deployment of new business, product/pricing and risk strategies into the decision engine; provide monitoring and auditing reports after deployment.
• Provide data support in response to one-time and recurring requests.
• Work with Technology to transform data from native formats into usable, readily available data.
• Monitor data quality and take corrective action; automate data quality monitoring and improve auditing capabilities.

Education

Master's degree in Finance (USA)

Job description

LendingUSA, LLC. is seeking a data analyst to design, implement, deliver and analyze enterprise data to produce actionable analytical insights and models for finance and risk teams.

You will conduct profitability and risk analyses to support business growth, product pricing and risk management; deploy new strategies into decision engines and monitor data quality and auditing capabilities. Collaborate with Technology to transform raw data into usable formats and respond to data requests.