SoFi
The role
We are looking for a Staff Data Scientist to join our Risk Analytics Modeling Team within Risk Analytics. This team member’s responsibilities include model development and performance monitoring supporting data-driven decision-making within our second line of defense. The Staff 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 Staff 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.
What you’ll do :
The Staff Data Scientist will help SoFi develop better data driven modeling solutions by :
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
What you’ll need :
6+ years of loss forecasting 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 have :
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
Compensation and Benefits
The base pay range for this role is listed below. Final base pay offer will be determined based on individual factors such as the candidate’s experience, skills, and location.
To view all of our comprehensiveand competitivebenefits, visit our Benefits at SoFi
page! Pay range :
$153,600.00 - $264,000.00 Payment frequency : Annual This role is also eligible for a bonus, long term incentives and competitive benefits. More information about our employee benefits can be found in the link above.
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page! Pay range :
$153,600.00 - $264,000.00 Payment frequency : Annual This role is also eligible for a bonus, long term incentives and competitive benefits. More information about our employee benefits can be found in the link above.
#J-18808-Ljbffr