Consumer Product Strategy Analyst III (Analytics & Model Development)

Bank of America•Utica, NY

12d•$83,800 - $127,000•Onsite

About The Position

At Bank of America, the Consumer Product Strategy Analyst III performs complex analysis and modeling to minimize loss exposure and negative impacts to the customer experience. The role uses systems and tools such as Excel, SAS, SQL, Tableau, and relational databases to provide analytical support for strategies, assess whether goals are being met, and propose policy and procedural changes within segmentation structures. It also evaluates data to assess potential fraud risk and develop mitigation strategies. The role applies data science, advanced analytics, and statistical techniques to identify trends, diagnose root causes, uncover insights, and recommend solutions that improve operational performance and business outcomes. It sources, validates, transforms, integrates, and governs data; develops dashboards, reporting solutions, data pipelines, ETL workflows, monitoring controls, and data quality frameworks; and uses analytics to support forecasting, scenario modeling, predictive analytics, anomaly detection, and decision-making. The analyst partners with business, technology, strategy, and operational stakeholders, supports Agile delivery and production solutions, and communicates findings and recommendations to technical and non-technical audiences, including senior leadership. Bank of America describes its approach as an in-office culture supporting collaboration, engagement, and career development, with flexibility based on role responsibilities and business needs. Employees currently working from home may apply, but selected candidates may be required to work onsite under the workplace excellence policy. The role is listed at locations in Hunt Valley, Maryland; Las Vegas, Nevada; Utica, New York; and Richmond, Virginia. It is a first-shift position with 40 hours per week. The annualized pay range is $83,800 to $127,000, based on experience, education, and skill set. The role is eligible for an annual discretionary incentive plan and benefits, including paid time off.

Requirements

Demonstrated ability to query, transform, analyze, and validate data using SQL, SAS, Python, or similar analytical programming languages.
Experience creating dashboards, visualizations, and reporting solutions using Tableau or similar business intelligence tools.
Advanced Excel proficiency, including data analysis, modeling, and data manipulation.
Working knowledge of statistical concepts and analytical methods for identifying trends, relationships, root causes, and business opportunities.
Ability to use data to solve business problems and translate findings into actionable recommendations.
Strong analytical, critical-thinking, and problem-solving skills, including ability to work with large and complex datasets.
Strong written and verbal communication skills, including ability to communicate technical concepts to technical and non-technical audiences.
Ability to manage multiple projects and priorities in a fast-paced, rapidly changing environment.
Strong organizational skills, attention to detail, and ability to deliver accurate, high-quality work with minimal supervision.
Ability to work independently and collaborate effectively with cross-functional teams.
Curiosity, ownership, adaptability, and a continuous learning mindset, including willingness to learn new technologies, automation tools, and AI-enabled capabilities.

Nice To Haves

Advanced analytical and quantitative skills and demonstrated ability to use data and metrics to identify root causes.
Experience with Python, SAS, R, machine learning, predictive modeling, or advanced statistical methods.
Experience with automation, ETL development, workflow orchestration, or AI-assisted analytics.
Experience with enterprise platforms such as SQL Server, Oracle, Teradata, Hadoop, Snowflake, Databricks, or cloud analytics platforms.
Experience with Agile, Jira, SDLC, UAT, and production deployment practices.
Bachelor's degree in Analytics, Statistics, Mathematics, Economics, Engineering, Computer Science, Finance, Operations Research, Data Science, or a related quantitative discipline.

Responsibilities

Recommend ways to help the business achieve desired outcomes and make informed decisions using data analysis.
Analyze financial models, market and financial data, and portfolio trends to assess product performance and improve portfolio risk, profitability, forecasting, and operational performance.
Lead coordination of product performance reports and updates for senior management.
Apply data science, advanced analytics, and statistical techniques to identify trends, diagnose root causes, uncover actionable insights, and recommend solutions.
Source, validate, transform, integrate, and govern data from workforce management, contact center, vendor management, productivity, forecasting, capacity planning, and performance management platforms.
Design, develop, and maintain dashboards, automated reporting, data pipelines, ETL workflows, monitoring controls, and data quality frameworks.
Use SQL, Python, statistical methods, and emerging AI capabilities for forecasting optimization, scenario modeling, predictive analytics, anomaly detection, and prescriptive decision-making.
Translate business problems into analytical approaches and data-driven solutions that improve efficiency, effectiveness, customer experience, and operational outcomes.
Partner with business leaders, strategy teams, technology partners, and operational stakeholders to define requirements, prioritize opportunities, and deliver analytics solutions.
Lead or participate in designing, developing, testing, implementing, and continuously improving reporting, analytics, forecasting, automation, and decision-support capabilities.
Establish scalable processes, reusable data assets, governance standards, documentation, and development practices with cross-functional teams.
Support Agile delivery through requirements gathering, solution design, sprint planning, user acceptance testing, deployment readiness, and production support.
Monitor and identify data quality, process, operational, and reporting risks, and implement controls and remediation strategies.
Communicate analytical findings, recommendations, risks, and opportunities to technical and non-technical audiences, including senior leadership.
Manage multiple initiatives and competing priorities while delivering accurate, timely, high-quality work in a changing environment.
Evaluate emerging technologies, automation opportunities, and AI-enabled capabilities to improve analytical effectiveness, operational efficiency, and business value.
Perform other duties as assigned.