Consumer Product Strategy Analyst III – Analytics & Model Development

📍 Job Overview

Job Title: Consumer Product Strategy Analyst III – Analytics & Model Development Company: Bank of America Location: Charlotte, North Carolina, United States (with other potential locations: Rio Rancho, New Mexico; Plano, Texas; Las Vegas, Nevada; Greensboro, North Carolina) Job Type: Full-Time Category: Analytics & Data Science (within Consumer Banking Client Services Operations) Date Posted: November 4, 2025 Experience Level: Mid-Level (estimated 2-5 years) Remote Status: Hybrid (with specified office presence requirements)

🚀 Role Summary

• This role is critical for driving operational excellence within Consumer Banking Client Services by providing advanced analytical and data science support.
• It focuses on optimizing resource planning and performance through data delivery, in-depth reporting, process automation, and leveraging AI for forecasting.
• The position requires a blend of data analysis and data science skills to source, interpret, and present complex data into actionable insights for executive stakeholders.
• A key aspect involves developing and maintaining scalable processes and best practices, ensuring data integrity, and collaborating cross-functionally to achieve business goals.

📝 Enhancement Note: The job title "Consumer Product Strategy Analyst III" might suggest a focus on product development, but the detailed description clearly places this role within the operational analytics and model development function of Consumer Banking Client Services. The "III" indicates a mid-to-senior level within this analytical track. The emphasis on "Analytics & Model Development" and "Resource Planning & Optimization" aligns this role with Sales Operations, Revenue Operations, or a specialized GTM Analytics function within a large financial institution.

📈 Primary Responsibilities

• Utilize Data Science and advanced Data Analysis techniques to identify performance trends, uncover actionable business insights, and pinpoint opportunities for operational improvements.
• Engage in collaborative reporting and design sessions with organizational stakeholders and business owners to define requirements and deliver comprehensive reports and executive-level dashboards.
• Develop and maintain scalable, automated processes and best practices for data extraction, transformation, and loading (ETL), contributing to operational efficiency initiatives.
• Source and query data from various relational databases (e.g., SQL Server, Oracle, Teradata, Hadoop) to perform detailed trend analysis, support reporting needs, and inform critical business decisions.
• Partner closely with Performance Optimization, Scheduling, and Strategic teams to deliver robust data insights and analysis that directly influence key decision-making and goal achievement.
• Validate the integrity, accuracy, and quality of data used for analysis and reporting to ensure reliable insights and recommendations.
• Manage multiple concurrent projects, effectively prioritizing tasks and shifting focus as needed to deliver accurate work within established deadlines in a dynamic environment.
• Participate actively in weekly Agile stand-up meetings, providing timely status updates and contributing to team progress tracking.
• Contribute to the assessment and development of tools and technologies to automate and streamline processes, enhancing overall operational effectiveness.
• Perform ad hoc data analysis as required to address specific business questions or support emergent projects, demonstrating flexibility and responsiveness.

📝 Enhancement Note: The responsibilities highlight a strong blend of technical data skills (SQL, Python, ETL) with business acumen and collaboration. The "Analytics & Model Development" aspect suggests involvement in building predictive models or optimizing existing ones for resource allocation and forecasting, which is a core Revenue Operations and Sales Operations function focused on efficiency and predictive capability.

🎓 Skills & Qualifications

Education:

• Bachelor’s degree is desired, particularly in a quantitative discipline such as Mathematics, Statistics, Economics, Business, Engineering, Finance, or Operations Research.

Experience:

• Estimated 2-5 years of professional experience in data analysis, data science, or a related quantitative field, with a focus on operations or strategy support.

Required Skills:

• Minimum 1 year of experience in SQL coding for data querying and manipulation.
• Proficiency in Tableau for data visualization, dashboard creation, and reporting.
• Demonstrated experience with Python and its statistical libraries for data analysis, understanding relationships within data, and potentially model development.
• Advanced proficiency in Microsoft Excel for data manipulation, analysis, and reporting.
• Strong written and oral communication skills, with the ability to articulate complex analytical findings to both technical and non-technical audiences.
• Proven ability to manage multiple projects simultaneously in a complex, fast-paced, and rapidly changing environment.
• Excellent time management and organizational skills to meet established deadlines.
• Capacity to work effectively both independently and as a collaborative member of a team.
• Strong analytical and problem-solving skills to identify root causes and propose effective solutions.
• A positive attitude and a demonstrated willingness to learn and adapt to new technologies and methodologies.

Preferred Skills:

• Advanced analytical and quantitative skills, with a proven ability to use data and metrics to identify root causes of business issues.
• Experience working with enterprise-level database systems such as SSMS, Oracle, Hadoop, and Teradata.
• Familiarity with Software Development Life Cycle (SDLC) concepts and project management tools like Agile and Jira.
• 2+ years of experience with SAS EG / SAS Studio, or R programming for statistical analysis and modeling.
• Experience with ETL tools like Alteryx for automating data processes.

📝 Enhancement Note: The required skills clearly point towards a data-centric role within operations. The combination of SQL, Tableau, and Python is a strong indicator of the technical depth expected for data analysis and visualization. Experience with SAS or R, and ETL tools like Alteryx, further solidifies this as a role focused on process automation and sophisticated data manipulation, common in advanced Sales Operations or Revenue Operations functions. The "Advanced analytical and quantitative skills" and "using data and metrics to identify root causes" are crucial for driving operational strategy.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Demonstrate successful projects involving data extraction, transformation, and loading (ETL) processes, showcasing automation capabilities.
• Provide examples of creating interactive dashboards and reports using tools like Tableau, highlighting data visualization best practices and key performance indicator (KPI) tracking.
• Showcase instances where analytical insights derived from data directly led to process improvements, cost savings, or revenue enhancement within an operational context.
• Include case studies that illustrate the application of statistical methods or basic data science techniques to solve business problems, such as trend analysis, forecasting, or root cause identification.
• Present examples of how data was used to inform strategic decisions or optimize resource allocation.

Process Documentation:

• Evidence of documenting analytical processes, data workflows, and reporting methodologies to ensure reproducibility and facilitate knowledge transfer.
• Examples of creating clear, concise documentation for business stakeholders explaining complex data, analytical findings, and recommended actions.
• Demonstrate an understanding of how to map and analyze existing processes to identify bottlenecks and areas for automation or optimization.

📝 Enhancement Note: For an Analyst III role in this domain, a portfolio is essential. It should not just list tools, but showcase the impact of analytical work. This means demonstrating how data analysis and model development translated into tangible business outcomes like improved efficiency (automation), better decision-making (insights, dashboards), and optimized resource utilization (forecasting, planning). The focus on process documentation is key for a role in a large, regulated environment like a bank.

💵 Compensation & Benefits

Salary Range:

• $82,100.00 - $125,600.00 annualized salary. Offers will be determined based on experience, education, and skill set.

Benefits:

• Industry-Leading Benefits package, comprehensive and tailored to employee needs.
• Access to Paid Time Off (PTO) for rest and rejuvenation.
• Resources and Support provided to employees to facilitate their contributions and professional development.
• Eligibility for an annual discretionary incentive plan, based on individual, team, and company performance.

Working Hours:

• Standard 40 hours per week.
• 1st shift (United States of America).

📝 Enhancement Note: The salary range provided is a strong indicator of a mid-level to senior analyst position within a major financial institution, aligning with the Analyst III title. The mention of "Discretionary incentive eligible" is common for analytical roles that have a direct impact on business performance. The benefits are described broadly but emphasize comprehensive support, which is typical for large corporations.

🎯 Team & Company Context

🏢 Company Culture

Industry: Financial Services (Banking) Company Size: Large Enterprise (Bank of America is one of the world's largest financial institutions, employing hundreds of thousands of people globally). This scale implies extensive resources, established processes, and opportunities for specialization. Founded: 1998 (formed through a series of mergers and acquisitions, with roots tracing back to 1784). This long history signifies stability, deep industry knowledge, and a robust corporate structure.

Team Structure:

• The role is within the "Analytics and Model Development team" under "Consumer Banking Client Services." This suggests a specialized analytics unit focused on supporting operational aspects of consumer banking, likely dealing with customer service, resource allocation, and performance management.
• The team likely comprises data analysts, data scientists, and potentially business intelligence developers, reporting up through a management structure focused on optimization and strategy within Consumer Banking.
• Collaboration is expected with other "Resource Planning & Optimization teams" and "organizational stakeholders and business owners," indicating a highly cross-functional working environment.

Methodology:

• The team utilizes a blend of Data Science and Data Analysis methodologies to extract insights and drive improvements.
• Agile methodologies are employed for project management and daily workflow, evidenced by participation in weekly Agile stand-up meetings.
• A strong emphasis is placed on data-driven decision-making, with a focus on performance trend analysis, process automation, and forecasting optimization using AI.
• The team leverages a sophisticated technology stack, including SQL, Python, Tableau, Alteryx, and SAS, for data manipulation, analysis, and visualization.

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

📝 Enhancement Note: Bank of America's culture emphasizes "Responsible Growth" and "Being a Great Place to Work." For operations and analytics roles, this translates to a focus on data integrity, ethical data use, efficiency, and collaborative problem-solving within a structured corporate framework. The "in-office culture" with flexibility suggests a hybrid model where collaboration and team synergy are valued, but individual work can be conducted with some autonomy.

📈 Career & Growth Analysis

Operations Career Level: Analyst III is a mid-level position, signifying a solid contributor capable of independent work on complex tasks and projects. It suggests a transition from execution-focused roles to those involving more strategic analysis, problem-solving, and potentially mentoring junior team members. Reporting Structure: The role reports into the Analytics and Model Development team within Consumer Banking Client Services. This team likely reports up through a Director or VP level responsible for operational analytics and strategy within that business unit. Collaboration will extend horizontally to various business stakeholders, including those in Performance Optimization, Scheduling, and Strategic planning. Operations Impact: This role has a direct impact on the efficiency and effectiveness of Consumer Banking Client Services operations. By providing data-driven insights, optimizing forecasts, and automating processes, the analyst contributes to better resource allocation, reduced operational costs, improved customer service delivery, and ultimately, enhanced profitability and client satisfaction for Bank of America.

Growth Opportunities:

• Specialization: Deepen expertise in specific analytical tools (e.g., advanced Python for ML, Alteryx for complex ETL) or statistical modeling techniques relevant to financial services.
• Career Progression: Advance to Senior Analyst, Lead Analyst, or Managerial roles within the Analytics & Model Development team or transition into related fields like Data Science, Business Intelligence, or Product Management within Consumer Banking.
• Skill Development: Opportunities to gain exposure to broader business strategies within Consumer Banking, enhance project management skills, and develop leadership capabilities through participation in cross-functional initiatives.
• Industry Exposure: Gain extensive experience in the financial services industry, understanding its unique data challenges and regulatory environment, which is highly valuable.

📝 Enhancement Note: The Analyst III title implies a solid foundation and the potential for significant growth. The emphasis on data science, AI, and model development suggests a forward-looking team, offering opportunities to work with cutting-edge analytical techniques. Progression within Bank of America can be substantial due to its size and diverse business units.

🌐 Work Environment

Office Type: The company emphasizes an "in-office culture" with requirements for office-based attendance, indicating a structured, collaborative work environment. Flexibility is allowed based on role-specific considerations, suggesting a hybrid model. Office Location(s): While Charlotte, NC is the primary listed location, the role also indicates potential for work in Rio Rancho, NM; Plano, TX; Las Vegas, NV; and Greensboro, NC. There is also mention of specific office locations in Hunt Valley, MD, and Utica, NY, suggesting that the role may be open to candidates in these locations as well, or that the job description is broadly applied. Workspace Context:

• The environment is likely collaborative, requiring regular interaction with team members and stakeholders across different departments.
• Access to robust IT infrastructure, including powerful workstations, secure network access, and a comprehensive suite of analytical tools and software.
• Opportunities for informal collaboration and knowledge sharing with peers through team meetings and dedicated project work. Work Schedule:
• A standard 40-hour work week on the 1st shift is expected.
• The hybrid nature of the role means a mix of in-office collaboration and remote work, requiring effective self-management and communication.

📝 Enhancement Note: The "in-office culture" note is significant. Candidates should expect to be in the office for a portion of the week, likely for team collaboration, meetings, and focused work requiring specific infrastructure. The multiple location options suggest a large, distributed team, but the hybrid expectation means local office presence is key.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: A recruiter or hiring manager will likely review applications and resumes, focusing on required technical skills (SQL, Tableau, Python) and relevant experience in analytics or data science.
• Technical Assessment: Expect a technical challenge or coding test, likely involving SQL queries, data manipulation in Python, or a data visualization task in Tableau, to assess practical skills.
• Hiring Manager/Team Interviews: Interviews with the hiring manager and potential team members will focus on behavioral questions, problem-solving scenarios, and assessing cultural fit. Be prepared to discuss past projects and how you handled specific challenges.
• Case Study Presentation: A common step for analytical roles is a case study where candidates are given a business problem and asked to analyze data, develop insights, and present recommendations. This will heavily involve your portfolio and your ability to articulate your thought process.
• Final Round: This may involve interviews with senior leadership to discuss strategic thinking, impact, and career aspirations.

Portfolio Review Tips:

• Quantify Impact: For each project, clearly state the problem, your approach, the tools used, and most importantly, the quantifiable results (e.g., "Reduced processing time by 15%", "Increased forecast accuracy by 10%", "Identified $X in cost savings").
• Showcase Tool Proficiency: Include examples demonstrating your mastery of required tools (SQL, Tableau, Python) and preferred tools (SAS, Alteryx). Visually appealing Tableau dashboards are a plus.
• Highlight Process Improvements: Detail projects where you automated manual tasks, streamlined workflows, or developed new analytical processes.
• Structure for Clarity: Organize your portfolio logically, perhaps by skill (SQL projects, Python models, Tableau dashboards) or by business impact. Provide concise summaries for each item.
• Tailor to the Role: Emphasize projects related to forecasting, resource planning, performance analysis, and operational efficiency, as these are core to the job description.

Challenge Preparation:

• Practice SQL: Be ready to write complex SQL queries, including joins, subqueries, window functions, and aggregation.
• Python for Data: Brush up on Python libraries like Pandas, NumPy, and potentially SciPy or Scikit-learn for data manipulation and statistical analysis.
• Tableau Dashboards: Understand how to build effective, interactive dashboards that tell a clear story with data.
• Problem-Solving Scenarios: Prepare to walk through your thought process for tackling analytical problems, explaining your assumptions and how you would validate your findings.
• Communication: Practice explaining technical concepts and analytical results clearly and concisely to a non-technical audience.

📝 Enhancement Note: The emphasis on "Analytics & Model Development" and "Consumer Banking Client Services" means interviewers will look for a strong analytical foundation, practical application of data science techniques, and the ability to translate complex data into actionable business strategies within a financial services context. A well-curated portfolio is crucial for demonstrating these capabilities.

🛠 Tools & Technology Stack

Primary Tools:

• SQL: Essential for data querying and manipulation across various database systems. Proficiency in advanced SQL techniques is expected.
• Tableau: Core tool for data visualization, dashboard creation, and interactive reporting.
• Python: Crucial for data analysis, statistical modeling, automation, and potentially machine learning tasks. Experience with libraries like Pandas, NumPy, and statistical packages is vital.
• Excel: Advanced proficiency required for data analysis, reporting, and ad hoc tasks.

Analytics & Reporting:

• SAS EG / SAS Studio: Preferred for statistical analysis and model development, indicating a potentially deep analytics environment.
• Alteryx: Highly desirable for ETL processes and workflow automation, indicating a focus on efficiency and advanced data preparation.
• Data Warehousing: Experience with enterprise data environments like SQL Server, Oracle, Teradata, and Hadoop is beneficial.
• Business Intelligence Platforms: Familiarity with creating and maintaining executive-level dashboards and reports.

CRM & Automation:

• While not explicitly a CRM role, understanding how operational data integrates with customer data is beneficial.
• ETL Tools: Alteryx or similar tools are key for automating data pipelines and operational processes.
• Project Management Tools: Familiarity with Agile and Jira for managing workflows and tracking project progress.

📝 Enhancement Note: The technology stack is robust and indicative of a sophisticated analytics and operations environment. Proficiency in SQL, Tableau, and Python is non-negotiable. Experience with SAS, Alteryx, and enterprise databases like Teradata and Hadoop will significantly strengthen an application. This stack is typical for roles focused on driving efficiency and insights within large financial operations.

👥 Team Culture & Values

Operations Values:

• Data-Driven Decision Making: A core tenet, emphasizing the use of analytics and metrics to inform all strategic and operational choices.
• Efficiency and Automation: A drive towards streamlining processes, reducing manual effort, and leveraging technology to enhance productivity.
• Collaboration and Teamwork: Working effectively across departments and with various stakeholders to achieve shared goals and foster a supportive environment.
• Continuous Learning and Improvement: Commitment to staying updated with the latest analytical techniques, tools, and industry best practices to drive ongoing enhancement.
• Client Focus: Ultimately, all operational efforts are geared towards improving the experience and value delivered to Bank of America's clients.

Collaboration Style:

• Cross-Functional Integration: Actively engaging with business units, IT, and other operational teams to gather requirements, share insights, and implement solutions.
• Data Storytelling: Effectively communicating complex analytical findings and recommendations to diverse audiences, including leadership, in a clear, concise, and compelling manner.
• Agile Methodology: Participating in regular team stand-ups, sprint reviews, and retrospectives to ensure transparency, adaptability, and continuous feedback loops.
• Knowledge Sharing: Contributing to a culture of learning by sharing expertise, best practices, and insights with team members.

📝 Enhancement Note: Bank of America's stated values of "Responsible Growth," "Client Focus," and "Teamwork" are directly reflected in the expected team culture. For an analytical role, this means a balance between rigorous, objective analysis and effective communication and collaboration to ensure insights are understood and acted upon.

⚡ Challenges & Growth Opportunities

Challenges:

• Data Complexity and Scale: Working with vast amounts of data from disparate systems within a large financial institution, requiring robust data management and analytical skills.
• Balancing Technical Depth with Business Acumen: Effectively translating complex analytical models and findings into clear, actionable insights that resonate with business stakeholders.
• Navigating a Large Corporate Structure: Understanding and adapting to established processes, policies, and stakeholder dynamics within a large, matrixed organization.
• Rapidly Evolving Technology: Keeping pace with advancements in data science, AI, and analytical tools to ensure the team remains at the forefront of innovation.
• Prioritization and Time Management: Managing multiple competing project demands and shifting priorities effectively in a dynamic operational environment.

Learning & Development Opportunities:

• Advanced Analytics Training: Access to internal and external training programs to deepen expertise in data science, machine learning, AI, and statistical modeling.
• Industry Certifications: Opportunities to pursue certifications relevant to data analytics, data science, or project management.
• Mentorship Programs: Participation in mentorship programs to gain guidance from experienced professionals within Bank of America.
• Cross-Functional Exposure: Opportunities to work on projects that span different business units, broadening understanding of the financial services landscape.
• Leadership Development: Potential to take on project leadership roles, mentor junior analysts, and develop strategic planning capabilities.

📝 Enhancement Note: The challenges presented are typical for advanced analytical roles in large enterprises. They offer significant opportunities for professional development, pushing candidates to grow their technical skills, business understanding, and strategic thinking.

💡 Interview Preparation

Strategy Questions:

• "Describe a time you used data analysis to identify an operational inefficiency and what steps you took to address it." (Focus on your process: problem identification, data sources, analysis method, insights, recommendation, and impact).
• "How would you approach building a forecast model for customer service call volume, considering factors like seasonality, marketing campaigns, and product launches?" (Discuss data sources, statistical methods, model validation, and assumptions).
• "Imagine you've discovered a discrepancy in a critical report. How would you investigate and resolve it?" (Emphasize your methodical approach to data validation and problem-solving).
• "How do you ensure the quality and integrity of data when performing analysis?" (Discuss data profiling, validation checks, and collaboration with data stewards).

Company & Culture Questions:

• "What do you know about Bank of America's commitment to Responsible Growth?" (Research the company's mission and values; connect it to data-driven decision-making and operational efficiency).
• "How do you approach collaboration with non-technical stakeholders?" (Provide examples of simplifying complex data concepts and building consensus).
• "Describe your experience working in an Agile environment." (Highlight your understanding of Agile principles and your role in stand-ups and sprints).
• "How do you stay updated on the latest trends in data science and analytics?" (Mention resources like industry publications, online courses, conferences).

Portfolio Presentation Strategy:

• Select High-Impact Projects: Choose 2-3 projects that best showcase your SQL, Tableau, and Python skills, and demonstrate tangible business impact, ideally related to operations, forecasting, or efficiency.
• Tell a Story: For each project, clearly articulate the business problem, your role, your methodology, the challenges you faced, your insights, and the measurable outcomes.
• Focus on "So What?": Don't just present data; explain what the data means and what actions should be taken based on your findings.
• Be Ready for Deep Dives: Anticipate questions about your technical choices, assumptions, and the limitations of your analysis.
• Showcase Dashboard Interactivity: If presenting Tableau dashboards, be prepared to demonstrate how users can interact with them to explore data.

📝 Enhancement Note: Interview preparation should focus on demonstrating a strong blend of technical proficiency, analytical rigor, and business communication skills. The ability to translate complex data into actionable strategies is paramount for this role. Be ready to discuss your portfolio in detail, highlighting impact and process.

📌 Application Steps

To apply for this operations position:

• Submit your application through the provided career portal link.
• Portfolio Customization: Curate your portfolio to prominently feature projects demonstrating your expertise in SQL, Tableau, and Python, with a focus on operational analytics, process automation, and forecasting. Quantify the business impact of your work.
• Resume Optimization: Tailor your resume to highlight keywords from the job description, such as "SQL," "Tableau," "Python," "Data Science," "ETL," "Automation," "Reporting," "Trend Analysis," and "Forecasting." Use action verbs and quantify achievements.
• Interview Preparation: Practice answering behavioral and technical questions. Prepare to walk through your portfolio projects, explaining your methodology and the impact of your work. Research Bank of America's operations and values.
• Company Research: Understand Bank of America's business model, its focus on "Responsible Growth," and the specific area of Consumer Banking Client Services. Familiarize yourself with their approach to data and analytics.

⚠️ 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.