Data Scientist I Client Protection Modeling

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.

Client Protection Shared Services Advanced Analytics is looking for an energetic and inquisitive data scientist to join our team and help us combat financial this role you will be expected to work on large and complex data science projects that entail working with both relational and graph these projects it is expected to collaborate with internal strategy technology product and policy partners to deploy advanced analytical solutions with the goal of reducing fraud losses lowering false positive impacts improving client experience and ensuring the Bank minimizes its total cost of fraud. Key responsibilities include applying knowledge of multiple business and technical-related topics and independently driving strategic initiatives large-scale projects and overall improvements.

Responsibilities:

• Work with complex database tables and datasets to extract transform and prepare data for model features and analytical workflows

• Complete end-to-end model development work ranging from supervised unsupervised and graph-based machine learning solutions to maximize detection of fraud or capture anomalous behavior

• Build models such as linear/logistic regression tree-based models (Random Forest Gradient Boosting) NLP and Time-series models

• Enable business analytics including data analysis trend identification and pattern recognition using advanced techniques to drive decision making insights

• Ensure proper documentation of datasets analytical methods and model assumptions to maintain reproducibility and transparency

• Perform advanced analytics to identify and prioritize densely connected fraud networks leveraging cross-portfolio and graph data

• Manage multiple priorities while ensuring quality and timeliness of work deliverables including data science products data analysis reports and data visualizations with the ability to work both independently and collaboratively in a team environment

• Manage relationships with multiple technology teams development team and line of business partners ensuring alignment of roadmaps project execution and risk management

• Support execution of large-scale projects such as model deployments and new project integrations by conducting advanced reporting and drawing analytical-based insights

• Coach and mentor peers to improve proficiency in a variety of systems and serve as a subject matter expert on multiple business and technical-related topics

• Deliver engaging and effective presentations in both in-person and virtual settings to communicate technical concepts and analytical results to a diverse set of internal stakeholders while building professional relationships that foster collaboration on work deliverables

• Maintain knowledge of the latest advances in the fields of data science and artificial intelligence to support business analytics

• Develop and tune graph algorithms to maximize detection of fraud

• Identify business trends based on economic and portfolio conditions and communicate findings to senior management

• 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

Required Qualifications:

• 3 years experience in data and analytics

• Must be proficient with SQL and one of SAS Python or Java

• Exposure to model development leveraging supervised and unsupervised machine learning (regression tree-based algorithms etc.)

• Problem-solving skills including selection of data and deployment of solutions

• Experience providing thought leadership developing deliverables and working with limited direction on complex problems to achieve project goals

• Effective communication and influencing skills

• Thrives in fast-paced and highly dynamic environment

• Intellectual curiosity and strong urge to figure out the whys of a problem and produce creative solutions

• Experience handling and manipulating data across its lifecycle in a variety of formats sizes and storage technologies to solve a problem (e.g. structured semi-structured unstructured; graph; Hadoop; Kafka)

• Expertise in data analytics and/or technical development lifecycles

Desired Qualifications:

• Advanced degree (Masters or Doctorate) preferably in STEM (Science Technology Engineering Math) business or finance

• 5 years of experience; work in financial services is very helpful with preference to fraud credit cybersecurity or other heavily quantitative areas

• Understanding of advanced machine learning methodologies including neural networks graph algorithms Generative AI and other techniques

• Experience using data science tools (e.g. H2O Spark Hadoop) and Graph Databases (e.g. Tigergraph or Neo4j)

• Familiarity using Git for version control and collaborative code development

• Experience engaging with cross-functional teams and in large multi-organization formal projects

• Understanding of computer science topics like automation code versioning computational complexity parallel processing requirements gathering testing methodologies and development lifecycle models like Agile

• Risk and Issue Management interpreting relevant laws rules and regulations

• Data visualization oral and written communication and presentation skills

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

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

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