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Quantitative Analyst/Data Engineer

Bank of America

Bank of America

IT, Data Science
Multiple locations
Posted on Saturday, November 18, 2023

Job Description:

The Chief Investment Office (CIO) is the centralized resource to access the latest insights and solutions across the enterprise. The CIO helps Advisors establish a disciplined investment process and offer goals-based strategies that are grounded in the best thinking of the Firm. The Chief Investment Office provides thought leadership on wealth management, investment strategy and global markets and delivering strategic and tactical investment advice and in-depth guidance on portfolio strategies. The team delivers portfolio management solutions by developing and maintaining robust frameworks, services and tools to deliver goals-based wealth management (e.g., asset allocation and portfolio construction; all asset classes), and managing discretionary single asset and multi asset portfolios, including solutions oversight and data analytics to support processes across the CIO and Investment Solutions Group and promote the development and sharing of data, modeling, resources, and overall intellectual processing.

We seek a teammate with the ability to design, construct, and analyze data pipelines to support our quantitative infrastructure with a passion for system architecture with an entrepreneurial mindset. The associate will have extensive interaction other teams within the Chief Investment Office (CIO) such as due diligence, portfolio construction, platform management, technology, and risk teams. The associate will be expected to manage multiple projects simultaneously and discover innovative solutions to complex problems.


They are expected to help manage the team’s overall ability to meet deadlines and milestones, and will actively lead and work to transition code, scripts, tables and processes in coordination with other Solutions Oversight & Data Analytics resources.  The associate will be expected to manage multiple projects simultaneously, discover innovative solutions to complex problems, elevate and improve existing processes and must be comfortable working in a fast-paced environment.


  • Analyze and organize raw data from different sources (Vendors, data delivery methods, etc.)
  • Maintain SQL databases.
  • Build data systems and pipelines
  • Automate reports and processes to run with varying frequencies.
  • Monitor and debug processes and report the problem to the corresponding responsible parties.
  • Communicate to technology the needs and specifications of processes.
  • Explore ways to enhance data quality, reliability, and efficiency
  • Identify opportunities for data acquisition
  • Develop analytical tools and programs
  • Collaborate with data scientists and architects on several projects
  • Perform unit tests and conduct reviews with other team members to make sure your code is rigorously designed, elegantly coded, and effectively tuned for performance.


Minimum Requirements

  • Bachelor's Degree in Computer Science, IT, or relevant field required.
  • At least 5+ years' experience in Extract, Transform, Load (ETL) and/or Extract, Load, Transform (ELT) processes.
  • Proficient in data engineering practices and have extensive experience of using design and architectural patterns.
  • Experience working with database management languages (SQL, NoSQL).
  • Extensive experience with object-oriented programing (OOP)/Scripting languages such as R, Python, Bash, and/or Matlab
  • Technical expertise with data models, data mining, and segmentation techniques.
  • Experience working in multiple technology deployment lanes (development through production) is required.
  • Experience working with Git/Bit Bucket and code versioning.
  • Extreme attention to detail and organizational prowess
  • Ability to work both independently and in teams on projects executing on-time and with precision.
  • Friendly, courteous, humble mindset, and willingness to work in a flat team organization.

Preferred additional qualifications

  • MS in Computer Science, Engineering, or relevant field
  • Data engineering certification (e.g IBM Certified Data Engineer) is a plus.
  • Familiarity with internal or vendor data (FactSet, Morningstar, Bloomberg) is a plus but not required.
  • Experience with creating visualization dashboards (Tableau)
  • Hands-on experience in database design is a plus.


1st shift (United States of America)

Hours Per Week: