Communications Manager, Financial Technology

SoFi•San Francisco, CA

About The Position

We are looking for a Senior Data Scientist to join our Loss Forecasting Modeling Team within the Risk Data Science team. This team member’s responsibilities include model development and performance monitoring supporting data-driven decision-making within our first line of defense. The Senior Data Scientist will play a key role in developing loss forecasting and CECL models across various SoFi products including but not limited to Personal Loans, Student Loans and Credit Cards. The Senior Data Scientist will contribute to the performance analysis of SoFi products using empirical measurements, develop quantitative and machine learning models to forecast losses and provide insights on the drivers for losses. She/He will also collaborate with the Business Unit, Finance, Accounting, Credit & Fraud Risk groups. This position requires knowledge of data analytics and modeling using Python and machine learning/analytical packages as well as strong problem solving and communication skills. The ideal candidate should have hands-on knowledge on common loss forecasting methodologies (e.g. econometrics modeling, survival modeling, state transition, Markov Chain etc.) and excellent knowledge of data science, statistical methodologies and machine learning models (e.g. linear regression, logistic regression, decision trees, gradient boosting, random forests, neural network, clustering analysis etc.). By joining SoFi, you'll become part of a forward-thinking company that is transforming financial services for the better. We offer the excitement of a rapidly growing startup with the stability of an industry leading leadership team.

Requirements

5+ years of statistical modeling experience with a Master’s or PhD degree in Statistics, Mathematics, Economics, Engineering, Computer Science, or a quantitative field
Proficient in Python, SQL & Tableau
Experienced in model development and data analysis
Excellent knowledge of data science, statistical methodologies and machine learning models, e.g. linear regression, logistic regression, decision trees, gradient boosting, random forests, neural network, clustering analysis etc.
Hands-on knowledge on common loss forecasting methodologies, e.g. econometrics modeling, discrete survival modeling, state transition, Markov Chain etc.
Strong communications and presentation skills
Someone who is highly motivated and drives change, is eager to learn and able to work collaboratively in a complex and fluid environment

Nice To Haves

Familiarity working with bureau sandbox data a plus
Experience with generating credit reporting dashboard a plus
Experience with developing and productionizing models in the AWS environment a plus

Responsibilities

Developing quantitative/machine learning models to forecast product losses
Aggregating and synthesizing datasets from multiple data environments
Analyzing complex datasets to understand the performance and drivers for losses across various products
Investigating external credit data to identify trends in the market and industry
Conducting loss sensitivity analysis
Automating models and analytical dashboards
Monitoring the models’ performance and re-calibrating the models as needed
Working with Business Units, Operations, Product, Capital Markets, Finance, Accounting and Risk partners to ensure correct loss expectations and trend of losses are communicated effectively and executed appropriately