Data Scientist 1

Job Description:

At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. Responsible Growth is how we run our company and how we deliver for our clients, teammates, communities and shareholders every day.

One of the keys to driving Responsible Growth is being a great place to work for our teammates around the world. We’re devoted to being a diverse and inclusive workplace for everyone. We hire individuals with a broad range of backgrounds and experiences and invest heavily in our teammates and their families by offering competitive benefits to support their physical, emotional, and financial well-being.

Bank of America believes both in the importance of working together and offering flexibility to our employees. We use a multi-faceted approach for flexibility, depending on the various roles in our organization.

Working at Bank of America will give you a great career with opportunities to learn, grow and make an impact, along with the power to make a difference. Join us!

Job Description Summary

This job is responsible for analyzing and interpreting large datasets to uncover potential revenue generation opportunities and develop effective risk management strategies. Key responsibilities include collaborating with key stakeholders to comprehend business problems, utilizing data gathering and analysis techniques to devise solutions, and presenting recommendations based on the findings. Job expectations include demonstrating flexibility, resilience, accountability, a disciplined approach, and a commitment to fostering responsible growth for the enterprise.

Job Description:
This job is responsible for analyzing and interpreting large datasets to solve business problems and develop effective risk management strategies. Key responsibilities include collaborating with key stakeholders to comprehend business problems, utilizing data gathering and analysis techniques to devise solutions, and presenting recommendations based on the findings. Job expectations include demonstrating flexibility, resilience, accountability, a disciplined approach, and a commitment to fostering responsible growth for the enterprise.

Responsibilities:

Performs business analytics, which includes data analysis, trend identification, and pattern recognition, using advanced techniques (e.g., machine learning, text mining, statistical analysis, etc.) to support decision-making and drive data-driven insights

Applies agile practices for project management, solution development, deployment, and maintenance

Creates and maintains technical documentation, capturing the business requirements and specifications related to the developed analytical solution and its implementation in production

Manages multiple priorities and maintains quality and timeliness of work deliverables such as quantitative models, data science products, data analysis reports, or data visualizations, while exhibiting the ability to work independently and in a team environment

Delivers engaging presentations and engages in both in-person and virtual conversations that effectively communicate technical concepts and analysis results to a diverse set of internal stakeholders, and develops professional relationships to foster collaboration on work deliverables

Mitigates risk by identifying potential issues and developing controls

Researches the latest advances in the fields of data science and artificial intelligence to support business analytics

Skills:

Adaptability

Attention to Detail

Business Analytics

Technical Documentation

Written Communications

Agile Practices

Application Development

Collaboration

Data Visualization

DevOps Practices

Artificial Intelligence/Machine Learning

Networking

Policies, Procedures, and Guidelines Management

Presentation Skills

Risk Management

Required Technical Skills

Degree demonstrating training and experience in data science including mathematical component (e.g., Computer Science, Statistics, Mathematics, Data Science)

2+ years of related work experience, such as deep analytics of large data, exploratory modeling

Advanced SQL proficiency

Good, applied statistics skills, such as distributions, statistical testing, feature engineering

Understanding of machine learning techniques able to demonstrate basic understanding of algorithms

General understanding of model governance at a regulated financial institution

Python proficiency

Desired Skills

Accessing data on Hadoop/Teradata

Agile Methodology and Artifacts, JIRA, Confluence content creation

Bitbucket (or other version control)

Additional Programming Languages, for example, SAS, R, C++, Julia

Graph database, Graph theory

Shift:

Hours Per Week: