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Bank Of America Sr Operations Manager 
India, Maharashtra, Mumbai 
787143881

11.06.2025

Process Overview*

The Financed Emissions Accounting & Reporting team, a part of the Global Financial Control-Corporate Sustainability Controller organization within the CFO Group, plays a critical role in supporting the calculation of asset level balance sheet Financed Emissions, which are integral to the Bank ’s goal of achieving Net-zero greenhouse gas emissions by 2050.

Responsibilities*

Data development & Operations: Research on data requirements, produce executive level and detailed level data summary, validate the accuracy, completeness, reasonableness, timeliness on the dataset and develop desktop procedures for BAU operations. Perform data review and test technology implementation for financed emissions deliverables. Execute BAU processes such as new data cycle creation, execute data controls and data quality processes. Produce data summary materials and walk through with leadership team.


Requirements*

Bachelor’s degree in data management or analytics, engineering, sustainability, finance or other related field OR master’s degree in data science, earth/climate sciences, engineering, sustainability, natural resource management, environmental economics, finance or other related field

Certifications If Any NA

Experience Range*

•Minimum 15+ years in Climate, Financed Emissions, finance, financial reporting

•Three (3) or more years of experience in statistical and/or data management and analytics and visualization (intersection with financial services strongly preferred)

Foundational skills*

  • Deep expertise in SQL, Excel, automation & optimization, and project management
  • Knowledge of data architecture concepts, data models, ETL processes
  • Deep understanding of how data process works and ability to solve dynamically evolving and complex data challenges part of day-to-day activities.
  • Knowledge of data architecture concepts, data models, ETL processes
  • Deep understanding of how data process works and ability to solve dynamically evolving and complex data challenges part of day-to-day activities.
  • Experience in extracting, and combining data across from multiple sources, and aggregate data to support model development.
  • Experience in multiple database environment such as Oracle, Hadoop, and Teradata
  • Deep expertise in SQL, Excel, Python, automation & optimization, and project management
  • Strong technical and visualization skills, with the ability to understand the business goals, needs, and be committed to delivering recommendations that will guide strategic decisions.
  • Knowledge on Alteryx, Tableau, R, (knowledge of NLP, data scraping and generative AI welcome)
  • Strong leadership skills and proven ability in motivating employees and promoting teamwork.
  • Excellent interpersonal, management, and teamwork skills.
  • High level of significant independent decision-making ability.
  • Highly motivated self-starter with excellent time management skills and the ability to effectively manage multiple priorities and timelines.
  • Demonstrated ability to motivate others in a high-stress environment to achieve goal.
  • Ability to effectively communicate and resolve conflicts by both oral and written communication to both internal and external clients.
  • Ability to adapt to a dynamic and evolving work environment.
  • Well-developed analytical and problem-solving skills.
  • Experience and knowledge of the principles and practices of management and employee development.
  • Ability to think critically to solve problems with rational solutions.
  • Ability to react and make decisions quickly under pressure with good judgment.
  • Strong documentation & presentation skills to explain the data analysis in a visual and procedural way based on the audience.
  • Ability to quickly identify risks and determine reasonable solutions.

Desired skills

  • Advanced knowledge of Finance
  • Advanced knowledge of Climate Risk

Work Timings*

Window 12:30 PM to 9:30 PM (9 hours shift, may require stretch during peak period)