Data Scientist I

Bank of America•Charlotte, NC

5d•Onsite

About The Position

At Bank of America, the Data Scientist I analyzes and interprets large datasets to identify potential revenue opportunities and develop risk management strategies. The role collaborates with stakeholders to understand business problems, applies data gathering and analytical techniques, and presents recommendations based on findings. It calls for flexibility, resilience, accountability, disciplined work, and a commitment to responsible growth. The Data Scientist develops analytical solutions for credit risk, fraud analytics, customer segmentation, and portfolio management. The position extracts, transforms, and analyzes large datasets from enterprise data platforms; builds dashboards, reports, and automated analytical workflows; supports credit risk scorecard development, monitoring, performance tracking, and stress testing; and conducts portfolio analytics, trend analysis, and loss forecasting. It also performs data quality validation, reconciliation, and process improvement, and may extend company data with third-party sources. The role is based at 525 Washington Blvd, Jersey City, New Jersey. Bank of America describes an in-office culture intended to support collaboration, engagement, and career development, with flexibility based on role responsibilities and business needs. The position is first shift, 40 hours per week. The annual pay range is $115,000 to $143,000, with offers determined by experience, education, and skill set. The role is eligible for an annual discretionary incentive plan and benefits, including access to paid time off.

Requirements

Master's degree or higher in Computer Science, Data Science, Statistics, Mathematics, Finance, or a related quantitative discipline.
Strong STEM background and knowledge of machine learning, NLP, deep learning, statistical modeling, quantitative analysis, forecasting, and data visualization.
At least 2 years of experience developing Tableau data visualizations, reports, and dashboards.
Proficiency in programming languages such as Python (including scikit-learn, pandas, and NumPy), SQL, SAS, R, MATLAB, or C/C++.
Prior experience with SQL and NoSQL databases and distributed computing.
Applied statistics skills, including distributions, statistical testing, and regression.
Strong business analysis and documentation skills, including requirements, process flows, and data lineage.
Ability to manage multiple and competing priorities.
Excellent written and verbal communication skills.

Responsibilities

Perform business analytics, including data analysis, trend identification, and pattern recognition using techniques such as machine learning, text mining, and statistical analysis.
Apply agile practices for project management, solution development, deployment, and maintenance.
Create and maintain technical documentation covering business requirements and specifications for analytical solutions and their production implementation.
Manage multiple priorities and deliver quality, timely quantitative models, data science products, data analysis reports, and data visualizations, working independently and collaboratively.
Present technical concepts and analytical results to internal stakeholders in in-person and virtual settings, and build professional relationships to support collaboration.
Identify potential issues and develop controls to mitigate risk.
Research advances in data science and artificial intelligence to support business analytics.
Develop analytical solutions for credit risk, fraud analytics, customer segmentation, and portfolio management.
Extract, transform, and analyze large datasets from enterprise data platforms.
Build dashboards, reports, and automated analytical workflows and solutions.
Support credit risk scorecard development, monitoring, performance tracking, and stress testing.
Perform data quality validation, reconciliation, and process improvement initiatives.
Conduct portfolio analytics, segmentation, trend analysis, and loss forecasting.
Extend company data with third-party information sources when needed.