Quantitative Finance Analyst

Bank of America•Jersey City, NJ

2d•Onsite

About The Position

This job is responsible for conducting quantitative analytics and modeling projects for specific business units or risk types. Key responsibilities include developing new models, analytic processes, or systems approaches, creating technical documentation for related activities, and working with Technology staff in the design of systems to run models developed. Job expectations include having a broad knowledge of financial markets and products.

Requirements

Bachelors or Masters in computer science, system analysis, Information Systems or related field.
1-3+ years of experience with Data Sourcing, Data Wrangling, Data Engineering or similar role
Strong process/systems analysis, design and documentation.
Strong analytical, critical thinking, and problem-solving skills.
Ability to monitor tight deadlines and adapt to unexpected requirement changes.
Strong Understanding of Risk Management and Data Management Principles
Experience in Product Management: Ability to visualize functionality within a product, work with cross functional teams to deliver, market the product, create Road Shows/Office Hours, and onboard the users
Experience in Project Management: Create concise project plans, Delivery Management, JIRA advanced user, Presentation Skills
Business and Data Analysis Skills: Create BRDs/DRDs, SQL Skills, Technical skills (Python etc.) is a plus, Data Quality/Profiling Awareness, Data Lineage Awareness
Business Analytics: Tableau Experience, Any BI Tool Experience
Finance/Risk Domain Experience
Stakeholder management and Communication Skills.

Nice To Haves

Familiarity with one of the following areas – Trading, Consumer Banking, Wealth Management, Transaction Banking
Understanding or experience of programming in SQL, C/C++, Java
Familiarity with databases, such as Oracle, Hadoop, etc.

Responsibilities

Performs end-to-end market risk stress testing including scenario design, scenario implementation, results consolidation, internal and external reporting, and analyzes stress scenario results to better understand key drivers
Supports the planning related to setting quantitative work priorities in line with the bank’s overall strategy and prioritization
Identifies continuous improvements through reviews of approval decisions on relevant model development or model validation tasks, critical feedback on technical documentation, and effective challenges on model development/validation
Supports model development and model risk management in respective focus areas to support business requirements and the enterprise's risk appetite
Supports the methodological, analytical, and technical guidance to effectively challenge and influence the strategic direction and tactical approaches of development/validation projects and identify areas of potential risk
Works closely with model stakeholders and senior management with regard to communication of submission and validation outcomes
Performs statistical analysis on large datasets and interprets results using both qualitative and quantitative approaches
This role will collaborate with the GRM Data Stewards, Data Users, Data Owners, and Technology Teams to understand and assess their data, processes, and technology to support strategic data initiatives, remediate deficiencies, and drive business requirements.
Consult with data stewards, process owners, subject matter experts, technical experts, end users and other stakeholders to gather information about the current and target state business process, data attributes and data sources, control features, interfaces with other systems required.
Document and provide definitions for processes and procedures, data models, data quality controls, data lineage, and data dictionaries using industry standard methods including business process descriptions, use cases, scenarios, diagrams, flow charts, etc.
Analyze information gathered from multiple sources, reconcile conflicts, segment high-level information into details, and abstract up from low-level information to a general understanding.
Assess and identify deficiencies against internal policies and standards or industry best practices, providing formal recommendations and requirements to remediate.
Collaborate and partner with technology teams, architects, and other key stakeholders to drive solutions which provide ongoing operational excellence and resiliency to metadata and control environment challenges.
Review and provide input to technical solution designs from a business point of view and recommend alternatives.
Communicate plans, progress and risks appropriately to the stakeholders and sponsors.