About the role:
As an Analytics Analyst, you will be one of Enova’s most valuable team members. You will develop, enhance and test the company’s models for use in forecasting problems such as default forecasting and customer lifetime value forecasting. You will perform analysis to derive insights from data and/or model outputs to recommend financial, operational, risk management or marketing strategies. You will organize and process data, derive patterns and insights, and communicate your findings to cross functional teams to solve business problems, provide requirements and support implementation. 

 What you’ll be doing:

• Develop statistical and machine learning models to solve high impact business problems such as volume forecasting, customer lifetime value prediction and macro-economic factor analysis. 
• Design and develop the data pipeline that powers the aforementioned models, and develop monitoring metrics and methods to ensure continued stability and accuracy of the model in production. 
• Derive insights and conclusions from data and modeling outputs to support decision making for stakeholders across the organization. 

We’re excited about you if you have:

• 1-3 years of experience in an Analytics position or related field.
• Advanced programming skills and the ability to write customized code for meaningful data analysis and modeling (Python and/or R).
• Experience with machine learning methods such as multivariate regression, tree based models, time series models, regularization techniques, and dimensionality reduction techniques.
• Experience working with relational databases such as SQL.
• Knowledge of statistical/econometric modeling.
• A Bachelor's degree in Analytics or equivalent experience.

About our Analytics Team:
We live and breathe data at Enova and our 100+ person Analytics team is at the heart of it all. They use cutting-edge machine learning and advanced modeling techniques to drive business value in a number of different ways. Depending on the team, that could mean building a state-of-the-art credit risk model; it could mean spotting patterns in data that indicate fraud; it could mean researching a brand new type of algorithm we’ve never even used before. Whatever it is, it’ll typically be used to make real-time decisions on our website. What makes us different from Analytics teams elsewhere? We’re language agnostic here which means YOU get to pick the tool that works best for you and the analysis at hand. The team primarily uses Python, R, SAS, and SQL but if you think another tool is right for your project, go for it.