Consumer Product Strategy Analyst II/III – Analytics & Model Development

📍 Job Overview

Job Title: Consumer Product Strategy Analyst II/III – Analytics & Model Development

Company: Bank of America

Location: Charlotte, North Carolina, United States (with opportunities in Rio Rancho, New Mexico; Plano, Texas; Las Vegas, Nevada; Greensboro, North Carolina)

Job Type: FULL_TIME

Category: Revenue Operations / Analytics / Data Science

Date Posted: April 30, 2026

Experience Level: 2-5 Years (Analyst II/III implies mid-level to senior analyst)

Remote Status: Hybrid (with in-office expectations)

🚀 Role Summary

• This role is critical for driving operational excellence within Consumer Banking Client Services by providing advanced analytical and data support for the Analytics and Model Development team.

• Key responsibilities include developing and optimizing data delivery, creating robust reporting, automating processes through ETL, and enhancing forecasting models with AI capabilities.

• The analyst will leverage a diverse technology stack including SQL, Python, Tableau, Excel, and potentially SAS/Alteryx to derive actionable insights from complex datasets.

• This position requires a strong blend of data science, data analysis, and business acumen to translate data trends into strategic recommendations for process improvement and operational efficiency.

📝 Enhancement Note: The "Analyst II/III" designation suggests a need for candidates with a solid track record and the ability to handle increasing complexity and autonomy, bridging mid-level execution with senior-level strategic contribution. The emphasis on "Analytics & Model Development" points towards a role that goes beyond basic reporting to include predictive modeling and optimization techniques.

📈 Primary Responsibilities

• Utilize Data Science and advanced Data Analysis techniques to identify performance trends, uncover root causes, and recommend actionable operational improvements within client services.

• Engage in weekly Agile stand-up meetings, providing clear and concise status updates on ongoing projects and initiatives.

• Collaborate effectively with organizational stakeholders and business owners in design sessions to develop and deliver executive-level reports and dashboards that align with strategic business goals.

• Partner with other developers and data professionals to build and maintain scalable processes, ensuring adherence to best practices in data management and analysis.

• Manage a portfolio of multiple projects simultaneously, adeptly shifting priorities while consistently producing accurate work and meeting established deadlines.

• Ensure the integrity and quality of all data used for analysis through rigorous validation processes, maintaining data governance standards.

• Actively partner with Performance Optimization, Scheduling, and Strategic teams to deliver critical data insights and analysis that inform strategic decision-making and drive goal achievement.

• Contribute to the automation of existing processes using ETL tools, fostering a culture of operational excellence and efficiency.

• Perform trend analysis on resource planning and performance data to identify areas for enhancement and optimization.

• Connect to various database systems (SQL Server, Oracle, Teradata, Hadoop) to query data, support reporting needs, and conduct deep-dive analyses.

📝 Enhancement Note: The responsibilities highlight a hands-on role requiring both technical execution (SQL, Python, Tableau) and strategic thinking (identifying improvements, informing decisions). The emphasis on collaboration and stakeholder management is crucial for success in translating analytical findings into business impact.

🎓 Skills & Qualifications

Education:

Experience:

• 2-5 years of relevant experience in analytics, data science, or a related quantitative field.

Required Skills:

• SQL Coding: 1+ years of experience writing complex SQL queries for data extraction and manipulation across various database systems.

• Tableau: 1+ years of experience developing interactive dashboards and reports for business stakeholders.

• Python: Experience with Python for data analysis, statistical modeling, and automation, including understanding relationships within data.

• Advanced Excel Proficiency: Strong skills in using Excel for data analysis, modeling, and reporting.

• Communication Skills: Strong written and oral communication skills, with the ability to articulate complex analytical findings to both technical and non-technical audiences.

• Project Management: Ability to manage multiple projects, prioritize effectively, and meet deadlines in a fast-paced environment.

• Analytical & Problem-Solving: Excellent analytical and problem-solving capabilities to identify root causes and propose solutions.

• Teamwork & Independence: Ability to work effectively both independently and as a collaborative member of a team.

• Attitude: Positive attitude and a strong willingness to learn and adapt.

Preferred Skills:

• Data Science & Advanced Analytics: Advanced analytical and quantitative skills with demonstrated ability in using data and metrics to identify root causes and drive business insights.

• Database Experience: Experience with SSMS, Oracle, Hadoop, and Teradata.

• Methodologies: Familiarity with SDLC (Software Development Life Cycle) and project management concepts and tools, such as Agile and Jira.

• Alternative Tools: 2+ years of experience with SAS EG / SAS Studio, or R.

• ETL Tools: Experience with ETL tools like Alteryx for automating data processes.

📝 Enhancement Note: The "II/III" designation implies that candidates with 1+ years might be considered for the II level, while 2-5+ years would align more with the III level, especially if they possess advanced skills in preferred qualifications. The emphasis on both SQL and Python indicates a need for versatile data manipulation and analysis capabilities.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Showcase projects demonstrating proficiency in SQL for data extraction and manipulation from diverse sources (e.g., SQL Server, Oracle, Teradata, Hadoop).

• Include examples of Tableau dashboards that effectively visualize complex data, highlight key trends, and provide actionable insights for business stakeholders.

• Present case studies of Python or SAS/R-based analyses that identified business opportunities, solved problems, or developed predictive models.

• Highlight any experience with ETL processes or automation initiatives, demonstrating efficiency gains or streamlined workflows.

Process Documentation:

• Detail any processes you have documented or optimized, focusing on workflow design, implementation of automation, and the measurement of performance improvements.

• For projects involving reporting or dashboard development, clearly outline the requirements gathering, design, development, and validation phases.

• Demonstrate an understanding of data integrity checks and quality assurance processes you have implemented or followed.

• Illustrate how you have collaborated with cross-functional teams to define business requirements and deliver data-driven solutions.

📝 Enhancement Note: For an Analyst II/III role in a financial institution, a portfolio that clearly articulates the impact of their analytical work on business outcomes (e.g., cost savings, revenue enhancement, efficiency gains) will be highly valued. Demonstrating an understanding of data governance and compliance is also crucial.

💵 Compensation & Benefits

Salary Range: $82,100 - $125,600 annualized salary.

Benefits:

• Discretionary Incentive Plan: Eligible for an annual discretionary award based on individual, team, and company performance.

• Paid Time Off: Access to paid time off resources and support.

• Health and Wellness Support: Comprehensive benefits package designed to support employee wellness.

• Career Development: Opportunities for learning, growth, and making an impact within the organization.

Working Hours:

• 40 hours per week, typically on the 1st shift (United States).

📝 Enhancement Note: The salary range provided is a strong benchmark for mid-level to senior analyst roles in the financial services sector in the US. The inclusion of a discretionary incentive plan is common for these roles, reflecting performance-driven compensation. The mention of "benefits eligible" suggests a standard package including health insurance, retirement plans, etc., though specific details are not itemized beyond PTO and wellness support.

🎯 Team & Company Context

🏢 Company Culture

Industry: Financial Services (Banking)

Company Size: Bank of America is one of the world's largest financial institutions, employing hundreds of thousands of people globally, indicating a large, established corporate environment with extensive resources and structured processes.

Founded: 1998 (through the merger of NationsBank and BankAmerica), with a lineage tracing back much further, suggesting a company with deep roots and a long history of evolution in the financial sector.

Team Structure:

• The Analytics and Model Development team is part of Consumer Banking Client Services, indicating a focus on customer-facing operations and support.

• This role will likely involve collaboration with other Resource Planning & Optimization teams, suggesting a matrixed or project-based team structure.

Methodology:

• The team utilizes Agile methodologies for project management, emphasizing iterative development and regular communication.

• Data-driven decision-making is paramount, with a focus on using analytics, data science, and AI for insights and forecasting.

• Operational excellence is a key driver, with initiatives focused on automation and process streamlining.

Company Website: https://www.bankofamerica.com/

📝 Enhancement Note: Bank of America's culture is characterized by a commitment to "Responsible Growth," aiming for sustainable business practices and positive societal impact. For operations roles, this translates to a focus on efficiency, data integrity, risk management, and ethical data usage. The "in-office culture" with flexibility indicates a hybrid model that requires in-person collaboration.

📈 Career & Growth Analysis

Operations Career Level: Analyst II/III - This level signifies a professional who has moved beyond entry-level tasks and is capable of independent work, complex problem-solving, and contributing to strategic initiatives. An Analyst II typically has 2-4 years of experience, while an Analyst III might have 4-7 years, demonstrating deeper expertise and project leadership. This role is positioned to make significant contributions to the efficiency and effectiveness of client services operations.

Reporting Structure: The role reports into the Analytics and Model Development team within Consumer Banking Client Services. This structure suggests a direct line of reporting to a manager overseeing analytics and data science initiatives for client services operations. Collaboration will extend to various cross-functional teams, including Performance Optimization, Scheduling, and Strategic teams.

Operations Impact: This role directly impacts operational efficiency, cost management, and client satisfaction by optimizing resource planning, automating processes, and providing data-driven insights. The development of better models and reports can lead to improved service delivery, reduced operational costs, and enhanced strategic decision-making within the Consumer Banking division.

Growth Opportunities:

• Skill Specialization: Deepen expertise in specific technologies like Python for AI/ML, advanced SQL, or specialized analytics platforms.

• Leadership Development: Progress to an Analyst III or Senior Analyst role, leading projects, mentoring junior analysts, and taking on more complex modeling challenges.

• Cross-Functional Mobility: Transition into roles within broader data science, business intelligence, or product strategy teams across different business units within Bank of America.

• Management Track: With demonstrated leadership and strategic impact, potential to move into management roles overseeing analytics teams.

📝 Enhancement Note: The "II/III" designation is key here. Candidates should assess their experience against typical benchmarks for these levels. For an Analyst III, demonstrating project leadership, mentoring, and a track record of significant impact on business outcomes will be crucial.

🌐 Work Environment

Office Type: Bank of America operates a hybrid work model, emphasizing an "in-office culture" with "specific requirements for office-based attendance" alongside "an appropriate level of flexibility." This suggests a structured approach to hybrid work, likely requiring several days per week in the office. The specific office locations listed (Charlotte, Rio Rancho, Plano, Las Vegas, Greensboro) indicate potential hubs for these operations teams.

Office Location(s):

• Charlotte, North Carolina (Primary location mentioned)

• Rio Rancho, New Mexico

• Plano, Texas

• Las Vegas, Nevada

Workspace Context:

• The environment is expected to be collaborative, with opportunities to work closely with other analysts, developers, and business stakeholders.

• Access to a robust technology stack and enterprise-level tools (SQL Server, Oracle, Teradata, Hadoop, Tableau, Python) is a given.

Work Schedule:

• Standard 40-hour work week, typically during the 1st shift (US business hours).

📝 Enhancement Note: While the role is designated as hybrid, the emphasis on "in-office culture" and "specific requirements" suggests that candidates should be prepared for a significant in-office presence. The exact number of days in the office may vary by team and role-specific considerations, but it's important to understand this expectation.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: HR or recruiter call to assess basic qualifications, interest, and cultural fit.

• Technical Assessment: May involve a coding challenge (SQL, Python) or a case study to evaluate analytical and problem-solving skills.

• Hiring Manager Interview: In-depth discussion about your experience, projects, and how you approach analytics and model development. Expect behavioral questions.

• Team Interviews: Meet with potential team members to assess collaboration style and technical depth.

• Final Interview: Often with a senior leader or director to discuss strategic alignment and overall fit.

Portfolio Review Tips:

• Quantify Impact: For each project, clearly state the problem, your approach, the tools used, and the measurable results (e.g., "reduced processing time by X%", "increased forecast accuracy by Y%", "identified Z dollars in potential savings").

• Showcase Technical Skills: Include examples that clearly demonstrate your proficiency in SQL, Python, Tableau, and advanced Excel. Highlight complex queries, data wrangling techniques, and sophisticated visualizations.

• Explain Your Process: For model development, explain the methodology used (e.g., statistical methods, AI algorithms), the data considerations, and how the model was validated.

• Tailor to the Role: Emphasize projects related to process automation, reporting, trend analysis, and forecasting, as these are core to the job description.

• Prepare to Discuss: Be ready to walk through your portfolio, articulating your contributions, challenges faced, and lessons learned for each project.

Challenge Preparation:

• SQL Proficiency: Practice writing complex queries involving joins, subqueries, window functions, and aggregations. Be prepared to optimize queries for performance.

• Python for Data Analysis: Refresh your knowledge of libraries like Pandas, NumPy, and Scikit-learn for data manipulation, statistical analysis, and basic model building.

• Tableau Visualization: Understand how to create clear, informative dashboards that tell a story and drive business decisions.

• Problem-Solving Scenarios: Prepare for hypothetical scenarios where you need to analyze data to solve a customer service or operational efficiency problem. Think about data sources, analytical approaches, and communication strategies.

📝 Enhancement Note: Given the financial industry context, expect a rigorous interview process that heavily scrutinizes technical skills, problem-solving abilities, and the ability to communicate complex findings clearly. A well-curated portfolio is essential for demonstrating practical application of skills.

🛠 Tools & Technology Stack

Primary Tools:

• SQL: Essential for data extraction, manipulation, and analysis across various database systems. Experience with SQL Server, Oracle, Teradata, and Hadoop is highly valued.

• Python: Crucial for data analysis, statistical methods, automation, and AI/ML model development. Familiarity with libraries like Pandas, NumPy, and Scikit-learn is expected.

• Tableau: Key for creating interactive dashboards and reports to visualize data and communicate insights to stakeholders.

• Advanced Excel: Necessary for data analysis, modeling, and ad-hoc reporting.

Analytics & Reporting:

• Data Science & Statistics: Experience with statistical methods and applying them to understand data relationships.

• ETL Tools: Experience with tools like Alteryx is preferred for automating data processes and streamlining workflows.

• Business Intelligence: General understanding of BI principles and how to leverage data for strategic decision-making.

CRM & Automation:

• SDLC & Agile: Familiarity with Software Development Life Cycle and Agile project management methodologies (including Jira) is a plus.

• Process Automation: Focus on using tools and techniques to automate manual processes and drive operational efficiency.

📝 Enhancement Note: The required tools (SQL, Tableau, Python, Excel) form the core technical skillset. Preferred tools like SAS, R, Alteryx, and specific database technologies (SSMS, Oracle, Teradata, Hadoop) can significantly differentiate candidates. Understanding how these tools integrate to support end-to-end analytical workflows is key.

👥 Team Culture & Values

Operations Values:

• Data-Driven Decision Making: A strong emphasis on using data and analytics to inform strategy and operational improvements.

• Operational Excellence: Commitment to efficiency, automation, and continuous process improvement within client services.

• Client Focus: Dedication to improving the client experience through better resource planning, service delivery, and support.

• Collaboration & Teamwork: Emphasis on working effectively across teams and with stakeholders to achieve common goals.

• Integrity & Risk Management: Adherence to high ethical standards and robust risk management practices, critical in the financial services industry.

Collaboration Style:

• Cross-Functional Integration: The role requires close collaboration with various departments (Performance Optimization, Scheduling, Strategic teams) to gather requirements, share insights, and implement solutions.

• Agile Environment: Expect a dynamic and iterative approach to projects, with regular communication and feedback loops.

• Stakeholder Management: Ability to effectively communicate with technical and non-technical stakeholders, translate business needs into analytical requirements, and present findings clearly.

📝 Enhancement Note: Bank of America's stated values of "Doing What's Right," "Putting Clients First," "Teamwork," and "Respect" are foundational. For operations roles, this translates to a focus on accuracy, reliability, client satisfaction, and ethical conduct in data handling and analysis.

⚡ Challenges & Growth Opportunities

Challenges:

• Data Complexity & Volume: Handling large, complex datasets from multiple sources within a regulated financial environment.

• Balancing Priorities: Managing multiple projects with shifting deadlines and stakeholder demands effectively.

• Translating Insights: Effectively communicating complex analytical findings and recommendations to diverse audiences, ensuring buy-in and action.

• Adapting to Technology: Staying current with evolving data science techniques, AI advancements, and new analytical tools.

• Navigating Corporate Structure: Understanding and working within the established processes and hierarchies of a large financial institution.

Learning & Development Opportunities:

• Advanced Analytics & AI: Opportunities to deepen knowledge and application of statistical methods, machine learning, and AI for forecasting and model development.

• Technology Stack Expansion: Gaining experience with a broader range of enterprise-grade data platforms and tools used by Bank of America.

• Project Leadership: Developing skills in project management and potentially leading analytical initiatives.

• Industry Knowledge: Deepening understanding of consumer banking operations, client services, and financial product strategies.

• Mentorship: Access to experienced professionals within the Analytics and Model Development team for guidance and professional development.

📝 Enhancement Note: The challenges presented are typical for an advanced analyst role in a large financial institution. The growth opportunities emphasize continuous learning and the potential for significant career advancement within the company's vast network.

💡 Interview Preparation

Strategy Questions:

• "Describe a complex analytical project you led from conception to completion. What was the business problem, your approach, the tools you used, and the measurable impact?" (Focus on quantifiable results and your specific contributions).

• "How would you approach building a predictive model to forecast customer service demand for a specific product line?" (Demonstrate your understanding of data sources, feature engineering, model selection, validation, and deployment considerations).

Company & Culture Questions:

• "What do you know about Bank of America's approach to Responsible Growth and client service?" (Show you've researched their mission and values).

• "How do you approach collaboration with different teams, especially when there are competing priorities?" (Emphasize teamwork, communication, and problem-solving).

Portfolio Presentation Strategy:

• Storytelling: For each portfolio piece, frame it as a narrative: the challenge, your role, the solution, and the outcome.

• Data Visualization: Be prepared to share your screen and walk through key dashboards or visualizations, explaining the insights they reveal and how they support business decisions.

• Quantify Everything: Always back up your claims with data and metrics. Show the ROI or business impact of your work.

• Technical Depth: Be ready to discuss the technical details of your projects, including challenges in data handling, modeling techniques, and tool choices.

📝 Enhancement Note: Prepare specific examples that align with the job description's focus on analytics, model development, automation, and client services. The interview process will likely test both your technical acumen and your ability to apply it strategically within a large financial institution.

📌 Application Steps

To apply for this operations position:

• Submit your application through the provided link on the Bank of America careers portal.

• Portfolio Customization: Select 2-3 key projects from your professional experience that best showcase your expertise in SQL, Python, Tableau, advanced Excel, data analysis, and model development. Ensure these projects highlight your ability to drive operational improvements and deliver measurable business impact.

• Resume Optimization: Tailor your resume to highlight keywords from the job description, such as "SQL," "Tableau," "Python," "Data Science," "Analytics," "Model Development," "ETL," "Automation," and "Forecasting." Quantify your achievements with specific metrics wherever possible.

• Interview Preparation: Practice articulating your project experiences using the STAR method (Situation, Task, Action, Result). Prepare answers for common behavioral and technical questions relevant to data analysis and model development in the financial services industry.

• Company Research: Thoroughly research Bank of America's mission, values, recent news, and their commitment to client service and responsible growth. Understand their business objectives and how this role contributes to them.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.