Quantitative Services Senior Professional (Data Science Team)

Key Skills

Java Programming, Finance, Python Programming, Database, SQL, Agile methodologies, Machine learning techniques, Data science techniques, Algorithms

Job Description

The Quantitative Services Data Science team develops solutions to improve operational processes at Bank of America. Qualified individuals should have experience working with machine learning models and the ability to work with business partners to define and execute the appropriate problem solving strategy that will result in meaningful impact. The right candidate understands when machine learning should be deployed versus other types of Robotic Process Automation that the QS team could offer and demonstrates an ability to develop machine learning systems that may incorporate human-in-the-loop or other techniques to lower model risk. The right candidate for the role has a demonstrated track record of having ownership of projects and see the modeling and deployment efforts through to completion.

This team values the intellectually curious individual that enjoys learning from their teammates as well as sharing what they have learned from others and through their own exploration.

Responsibilities:

• The candidate is expected to work closely with the business analysts, business partners and other technology partners to gather requirements and successfully build, test and document machine learning solutions.
• Work with stakeholders to understand the problem statement and propose the appropriate solution.
• Use proprietary and open source machine learning libraries for developing supervised, unsupervised, and deep learning based solutions.
• Actively participate in all aspects of the model development lifecycle.
• Produce rapid prototypes to explore viable use cases for full model development routines.
• Conduct business and statistical analysis on bank owned data.
• Develop effective business solutions based on business needs.
• Prepare model document for the solutions you develop.

Requirements:

•  5+ years relevant industry experience.
• Minimum of 2 years of Python programming experience.
• Experience building a variety of machine learning models, including hyper parameter tuning, sensitivity analysis, model performance and accuracy evaluation, and incorporation of models into production processes.
• Experience building machine learning systems that include meta-learners, final decision algorithms, or other techniques deployed in stacked machine learning systems.
• Strong technical background with proven experience working in an Agile software development lifecycle.
• Experience with both SQL and noSQL database technologies.

Highly preferred:

• Master’s degree or higher in Computer Science, Data Science, Mathematics, Financial Engineering, Economics or related quantitative field.
• Experience in Fraud Models

Other Qualifications:

• Strives to bring new thoughts and ideas to teams in order to drive innovation and unique solutions.
• Excels in working among diverse viewpoints to determine the best path forward.
• Experience in connecting with a diverse set of clients to understand future business needs – is a continuous learner.
• Commitment to challenging the status quo and promoting positive change.
• Participate in and drive collaborative efforts to advance tools, technology, and ways of working to better serve an evolving client base.
• Believes in value of diversity so we can reflect, connect and meet the diverse needs of our clients and employees around the world.