Data Scientist I

Atlanta, GA, United States

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:

As a “Data Scientist I” supporting Enterprise Information Product maintenance, enhancement, and development, the associate will play a pivotal role in ensuring the accuracy, efficiency, and relevance of our data-driven solutions. Collaborating closely with cross-functional teams, the associate will contribute to the enhancement and optimization of our existing products while assisting in the development of new offerings to address emerging challenges and opportunities within the organization.

Responsibilities:

1. Data Analysis: Conduct thorough analysis of large datasets to extract actionable insights and identify trends relevant to our information products.

2. New Project Development: Assist in the development and refinement of rule-based SQL logics, algorithms, and statistical techniques to improve the performance and effectiveness of our products.

3. Product Maintenance: Proactively monitor the performance of existing information products, troubleshoot issues, and implement necessary updates and enhancements.

4. Data Visualization: Create compelling visualizations and reports to communicate findings and facilitate understanding of complex data concepts for both technical and non-technical stakeholders.

5. Collaboration: Work closely with cross-functional teams including software engineers, product managers, and business analysts to ensure alignment of data science initiatives with business objectives.

6. Documentation: Maintain thorough documentation of methodologies, processes, and outcomes to support reproducibility and knowledge sharing within the team.

7. Continuous Learning: Stay abreast of industry trends, emerging technologies, and best practices in data science and analytics to continuously enhance skills and contribute to the advancement of our capabilities.

Skills:

Attention to Detail

Business Analytics

Technical Documentation

Agile Practices

Application Development

DevOps Practices

Artificial Intelligence/Machine Learning

Networking

Policies, Procedures, and Guidelines Management

Presentation Skills

Qualifications:

- Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related field.

- 3+ years of data driven analytical experience; if Masters or above, 1+ years of experience

- Solid understanding of data analysis techniques, machine learning algorithms, and statistical methodologies.

- Proficiency in programming languages such as SAS, Python, R, or SQL.

- Experience with data visualization tools such as Tableau, Power BI, or matplotlib.

- Experience of managing projects and tasks in JIRA, Confluence, and SharePoint.

- Ability to thrive in a fast-paced, dynamic environment and adapt to evolving priorities and requirements.

Preferred Qualifications:

- Previous experience working with enterprise information products or data-driven solutions.

- Familiarity with big data technologies and frameworks such as Hadoop and Teradata.

- Knowledge of database systems and data warehousing concepts.

- Experience in cleaning, reprocessing, and exploring large datasets.

- Certification in data science or related fields is a plus.

Shift:

1st shift (United States of America) 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:

As a “Data Scientist I” supporting Enterprise Information Product maintenance, enhancement, and development, the associate will play a pivotal role in ensuring the accuracy, efficiency, and relevance of our data-driven solutions. Collaborating closely with cross-functional teams, the associate will contribute to the enhancement and optimization of our existing products while assisting in the development of new offerings to address emerging challenges and opportunities within the organization.

Responsibilities:

1. Data Analysis: Conduct thorough analysis of large datasets to extract actionable insights and identify trends relevant to our information products.

2. New Project Development: Assist in the development and refinement of rule-based SQL logics, algorithms, and statistical techniques to improve the performance and effectiveness of our products.

3. Product Maintenance: Proactively monitor the performance of existing information products, troubleshoot issues, and implement necessary updates and enhancements.

4. Data Visualization: Create compelling visualizations and reports to communicate findings and facilitate understanding of complex data concepts for both technical and non-technical stakeholders.

5. Collaboration: Work closely with cross-functional teams including software engineers, product managers, and business analysts to ensure alignment of data science initiatives with business objectives.

6. Documentation: Maintain thorough documentation of methodologies, processes, and outcomes to support reproducibility and knowledge sharing within the team.

7. Continuous Learning: Stay abreast of industry trends, emerging technologies, and best practices in data science and analytics to continuously enhance skills and contribute to the advancement of our capabilities.

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

Qualifications:

- Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related field.

- 3+ years of data driven analytical experience; if Masters or above, 1+ years of experience

- Solid understanding of data analysis techniques, machine learning algorithms, and statistical methodologies.

- Proficiency in programming languages such as SAS, Python, R, or SQL.

- Experience with data visualization tools such as Tableau, Power BI, or matplotlib.

- Experience of managing projects and tasks in JIRA, Confluence, and SharePoint.

- Ability to thrive in a fast-paced, dynamic environment and adapt to evolving priorities and requirements.

Preferred Qualifications:

- Previous experience working with enterprise information products or data-driven solutions.

- Familiarity with big data technologies and frameworks such as Hadoop and Teradata.

- Knowledge of database systems and data warehousing concepts.

- Experience in cleaning, reprocessing, and exploring large datasets.

- Certification in data science or related fields is a plus.

Shift:

1st shift (United States of America) Hours Per Week:

40

About Us Bank of America is committed to help employees through the transition period when they’re displaced as a result of a workforce reduction, realignment or similar measure. Please review the resume writing and interviewing tips provided below to help prepare you for your next career opportunity.

Regardless of the position you are interested in, the starting points to building your resume are the same:

1. Determine the job or types of jobs you want to do and research their responsibilities and qualifications.

2. Think about why you can do the job and make a list of your skills that are relative to the job.

3. Identify experiences or accomplishments that show your proficiency in the skills required for the job.

4. Summarize your abilities, accomplishments and skills into a brief, concise document.

Considerations when writing a resume

• Do be brief. Resumes should be 1-2 pages in length.

• Do be upbeat and active in your wording.

• Do emphasize what you have done clearly and concretely.

• Do be neat and well organized.

• Do have others proofread and critique your resume. Spell check. Make it error free.

• Do use high quality, white or light colored 8½ x 11 paper. Use a laser printer if possible.

• Don't be dishonest, always tell the truth about yourself in the most flattering light.

• Don't include salary history or requirements.

• Don't include references.

• Don't include accomplishments that do not support your professional goals.

• Don't include anything that isn't relevant. (For example, don't mention your fondness for swimming unless you want to work on the water.)

• Don't use italics, underlining, shadows or other fancy treatments.

Seven steps to a successful interview

1. Anticipate –Put yourself in the interviewer's position. What do you believe the interviewer is most interested in? Why do you think you have been invited to interview?

2. Research –What are the primary functions of the line of business? What are the success factors for the job? Is there a job description available?

3. Assess –Think about your skills, abilities, knowledge, interests, traits, values and accomplishments. Match them to what you know about the job. Consider which ones you should highlight.

4. Prepare Answers –Think about what the interviewer may ask, determine what the best answer is and write it down.

5. Prepare Questions – Interviewing is a two-way street. By asking thoughtful questions, you communicate your interest and learn a lot about the job. Choose two or three questions to ask your interviewer. Avoid asking a lot of questions about vacation time or breaks.

6. Practice – It may seem awkward, but it is the best way to come across well in an interview. Practice your own "great responses" with others or in front of a mirror until you appear relaxed and at ease.

7. Follow-up – Send a brief follow-up letter to the interviewer. Keep in mind that the many job searchers will not send a follow-up letter. Sending one can become a competitive advantage.

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