Staff Data Scientist
Staff Data Scientist
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1 Vacancy
Job Description
The role:
We are looking for a Staff Data Scientist to join our Risk Analytics Modeling Team within Risk Analytics. This team members 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 youll 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 youll 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 youll need:
- 6 years of loss forecasting experience with a Masters 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
Required Experience:
Staff IC
Employment Type
Full-Time
