Data Scientist I

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. We do this by driving Responsible Growth and delivering for our clients, teammates, communities and shareholders every day.

Being a Great Place to Work is core to how we drive Responsible Growth. This includes our commitment to being an inclusive workplace, attracting and developing exceptional talent, supporting our teammates’ physical, emotional, and financial wellness, recognizing and rewarding performance, and how we make an impact in the communities we serve.

Bank of America is committed to an in-office culture with specific requirements for office-based attendance and which allows for an appropriate level of flexibility for our teammates and businesses based on role-specific considerations.

At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us!
 

Job Description:
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.

Position Summary:

• Choosing best of breed ML solution and AI vendors by objective vendor evaluation; 
• Part of the AI governance initiative to ensure responsible AI/ML use in the bank; 
• Developing tailor made ML solutions to different uses cases inside technology infrastructure services and across the bank; 
• Designing and executing Proof of Concept projects related to Machine Learning; 
• Ability to practically implement ML techniques on business data such as data analysis processes and into the building predictive models; and, 
• Preparing ML environments for development and execution of models by installing packages and modules such as Anaconda, scikit-learn, NLTK, Keras, spaCy, and PyTorch; 
• Deploy and maintain machine learning models in production and manage ML model source code using Git/Bitbucket.

• Designing and developing Machine Learning solutions using for various business cases on the cloud infrastructure. 
• Installing packages and modules using Anaconda, scikit-learn, NLTK, Keras, spaCy, and PyTorch. 
• Use PyTorch and LLM (Large Language Models) to develop/tune conversational bots for different use cases.
• Designing and executing Proof of Concept projects using Machine Learning models, Redis, Kafka, Tiger Graph and Elastic Search.

Required Qualifications

• 5+ years of industry experience and 5+ years in the Data domain 
• BS/MS degree in Computer Science highly preferred
• In-depth, hands-on experience doing AI modeling, query optimizations and work in Python, and related technologies. 
• Exceptional communication skills with the ability to engage effectively with both technical and non-technical stakeholders 
• Experience with ETL or Streaming data and one or more of, Kafka, HDFS, Apache Spark 
• Extensive experience in data engineering and working with Big data

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

Shift:

Hours Per Week: