Data Scientist I

Job Description:

Role Overview:

The data science team in Global Risk Analytics works on data science projects that leverage Bank of America proprietary data to create information advantage to enable revenue creation, cost saving, and risk mitigation. We are looking for a Data Scientist who will help us discover the information advantage hidden in vast amounts of data, and help us make smarter decisions to deliver better products and services. Your primary focus will be in applying data science techniques to the bank’s proprietary customer transaction and relationship data to produce high frequency economic indicators and customer portfolio performance metrics, including consumer spending, payroll, unemployment, consumer credit, loan performance, etc. and stories of interest to external investors and economists, as well as internal senior management.

Key Responsibilities:
•    Individual contributor role practicing and enabling data science at Bank of America
•    Works with senior data scientists in the team on data science projects
•    Interacts with business partners to develop analytic stories about consumer cash flow, spending, and credit behavior
•    Works with cross-functional teams in GRA on the development, production, and maintenance of Enterprise Information Products
•    Performs tasks of data wrangling and feature engineering
•    Extends company’s data with third party sources of information when needed
•    Ensures data integrity for analysis and modeling
•    Data visualization and communications of data-driven insights

Experience / Qualifications:
•    Advanced Degree in a STEM discipline like computer science, Engineering, Statistics, Mathematics, Bioinformatics etc. 
•    2+ years of professional experience as a data scientist or related roles
•    2+ years of working with customer transaction and relationship data for large financial institutions
•    Strong SQL skills for large relational databases (Teradata, DB2, Oracle, etc.)
•    Experience with distributed computing (Hadoop, Spark, etc.)
•    Strong SAS programming skills
•    Proficiency in Python and/or R 
•    Ability to navigate enterprise data assets across multiple domains
•    Strong attention to detail and curiosity about data anomalies
•    Ability to collaborate within and between cross-functional teams
•    Ability to manage multiple and competing priorities
•    Excellent written and verbal communication skills
•    Experience in credit risk management, statistical modeling, and time-series forecast preferred
 

Shift:

1st shift (United States of America)

Hours Per Week: 

40