Data Scientist II

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:
This Data Scientist II individual will be required to discover the information advantage in vast amounts of proprietary data. For this position, we want someone with outstanding data wrangling skills and good knowledge of end-to-end modeling process.   This person will work with business experts and technical partners to provide clean, well-structured data for modeling. You will use statistical analysis, graph theory and modeling techniques. This position may build models to support data curation, feature building and testing processes. As a Data Scientist II, you will lead through personal influence across multiple disciplines, make recommendations and independent decisions.

Key Responsibilities:
• Learn financial products and how data represent BAML interactions with customers and clients
• Prepare data for analytics: clean, design, move, and test huge data stores (files, tables on Teradata or Hadoop or UNIX file system)
• Research opportunities for data acquisition and discover new uses for existing data
• Provide data that are friendly, trustworthy and high quality
• Employ a variety of languages and tools to marry systems together
• Perform tasks of data wrangling and feature engineering
• Recommend ways to improve data reliability, efficiency and quality

• Responsible for enabling analysis, modeling, and optimization through producing information products. Actively involved in the research and development efforts. Primary requirement is not related to traditional programming or systems analysis skills, but to the ability to create sophisticated, value-added analytic systems that support revenue generation, risk management, operational efficiency, regulatory compliance, portfolio management, and research. These systems must overcome issues of complex data (e.g., VLDB, multi-structured, big data, etc.) as well as deployment of advanced techniques (e.g., machine learning, text mining, statistical analysis, etc.) to deliver insights. This role often possesses a degree in hard science or another heavy quantitative business or social discipline. Able to work independently on complex projects.

Skills:

• Agile Practices
• Application Development
• DevOps Practices
• Technical Documentation
• Written Communications
• Artificial Intelligence/Machine Learning
• Business Analytics
• Data Visualization
• Presentation Skills
• Risk Management
• Adaptability
• Collaboration
• Consulting
• Networking
• Policies, Procedures, and Guidelines Management

Required Business Skills:
• Creative Problem-Solving: Approach data and modeling challenges with a clear eye on what is important; employ the right approach/methods to maximize time and human resources.
• Effective Collaboration: Carefully listen to business partners, analysts, and other modelers to establish requirements and ensure proper representation of information for models.
• Discipline and Organization: Apply structure and order to communication and documentation for data products and Model Management. Minimize risk by following best practices.
• Listen and Learn: Listen to experts, have a curious and exploring nature, continually push self to learn, receive constructive feedback well.
 

Qualifications:

• 5+ years of related work experience, such as deep analytics of large data, exploratory modeling
• Strong SQL skills are necessary.
• Basic applied statistics skills, such as distributions, statistical testing, feature engineering
• Able to demonstrate basic understanding of modeling algorithm.

Desired Qualifications:

• Accessing data on Hadoop
• Agile Methodology and Artifacts, JIRA, Confluence content creation
• Bitbucket (or other version control)
• Python and/or SAS Programming

Shift:

1st shift (United States of America)

Hours Per Week: 

40