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Data Support Manager

Pay
$109,100–203,500/year — pay source
Pay range $109,100.00 - $203,500.00 annualized salary, offers to be determined based on experience, education and skill set. Discretionary incentive eligible
Read the full posting
Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

What you’ll work on

Full posting
  • Build agentic AI solutions using LLMs, retrieval-augmented generation and tool calling

  • Develop Python services, reusable libraries, data pipelines and APIs across multiple systems of record

  • Create evaluation frameworks for ML and generative AI solutions

  • Implement human-in-the-loop controls, guardrails and audit trails for agentic workflows

  • Document end-to-end data lineage from sources through models, prompts and outputs

From the employer’s posting
Build agentic AI solutions that use large language models, retrieval-augmented generation, tools, APIs and workflow orchestration
Develop robust Python services, reusable libraries, data pipelines and APIs that integrate structured and unstructured data from multiple Systems of Record.
Create evaluation frameworks for ML and generative AI solutions
Implement appropriate human-in-the-loop controls, guardrails, audit trails, access controls, fallback paths and approval checkpoints for agentic workflows.
Document and maintain end-to-end data lineage from source systems through transformations, features, models, prompts, agent actions and downstream outputs.

What you’ll bring

All qualifications

Core experience

  • Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Engineering, Statistics, Mathematics or a related quantitative discipline.
  • 5+ years of professional experience building data analytics, machine learning or AI solutions, with demonstrated ownership of solutions beyond experimentation and into production.
  • Practical knowledge of supervised and unsupervised learning, model selection, benchmarking, error analysis and explain ability.
  • Hands-on experience building and deploying generative AI or agentic AI solutions using LLMs, retrieval-augmented generation, embeddings, vector search, tool calling, prompt management, multi-step orchestration using LangGraph and MCP
  • Experience designing production data/ML pipelines and services using technologies such as SQL, Spark, Airflow, Databricks, REST APIs, Git, Docker and CI/CD.
  • Experience working with relational and NoSQL stores, large and heterogeneous datasets, and structured and unstructured information.
Qualification wording
Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Engineering, Statistics, Mathematics or a related quantitative discipline.
5+ years of professional experience building data analytics, machine learning or AI solutions, with demonstrated ownership of solutions beyond experimentation and into production.
Practical knowledge of supervised and unsupervised learning, model selection, benchmarking, error analysis and explain ability.
Hands-on experience building and deploying generative AI or agentic AI solutions using LLMs, retrieval-augmented generation, embeddings, vector search, tool calling, prompt management, multi-step orchestration using LangGraph and MCP
Experience designing production data/ML pipelines and services using technologies such as SQL, Spark, Airflow, Databricks, REST APIs, Git, Docker and CI/CD.
Experience working with relational and NoSQL stores, large and heterogeneous datasets, and structured and unstructured information.
Education & alternatives
Required Skills: - Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Engineering, Statistics, Mathematics or a related quantitative discipline. - 5+ years of professional experience building data analytics, machine learning or AI solutions, with demonstrated ownership of solutions beyond experimentation and into production.

Benefits in the posting

Full benefits wording
  • This role is currently benefits eligible. We provide industry-leading benefits, access to paid time off, resources and support to our employees so they can make a genuine impact and contribute to the sustainable growth of our business and the communities we serve.

From the employer’s posting.

Apply at Bank of America

Posting record

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Actively hiringFirst seen by us 2 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 2, 20262 days ago
Recorded sightings
3
Last seen by us
Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

In line with similar jobs

$109K–$204K against $154K–$225K, the middle half of what similar US postings state.

From 2,958 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 2

Early. Similar jobs usually come down between day 7 and day 53.

From 7,854 similar postings that came down. Coming down is not always a hire.

Bank of America is hiring

22 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring at a steady pace
  • Takes jobs down at a usual pace
  • 5% of open jobs were reposted
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • Databricks
  • Delta Lake
  • Docker
  • Iceberg
  • NoSQL
  • Snowflake
  • Spark
  • Airflow
  • NumPy
  • pandas
  • PyTorch
  • scikit-learn
  • TensorFlow
Where the posting names them
Under the GRM Data Strategy & Management leadership team, the Data Analyst / AI Engineer will design, build and operationalize quantitative models and agentic AI solutions for complex risk and data-management use cases. This is a hands-on role for an experienced practitioner who can move from problem framing and data discovery through experimentation, production deployment, monitoring and continuous improvement. The role will partner with risk subject-matter experts, data owners, technology teams and governance partners to deliver explainable, scalable and controlled solutions in a highly regulated environment. The successful candidate will combine strong Python and data engineering skills with basic understanding of data strategy, data lineage, metadata, data quality and data governance. The candidate should be able to translate business and control objectives into production-grade data and AI products, while documenting data provenance, model behavior, decisions and human oversight. Responsibilities:
- Build agentic AI solutions that use large language models, retrieval-augmented generation, tools, APIs and workflow orchestration to support research, analysis, decision support and operational processes. - Develop robust Python services, reusable libraries, data pipelines and APIs that integrate structured and unstructured data from multiple Systems of Record. - Create evaluation frameworks for ML and generative AI solutions, including accuracy, precision/recall, robustness, latency, cost, hallucination, groundedness and task-completion measures.
- 5+ years of professional experience building data analytics, machine learning or AI solutions, with demonstrated ownership of solutions beyond experimentation and into production. - Advanced hands-on Python development, including clean, testable and modular code; experience with pandas, NumPy, scikit-learn and at least one deep-learning framework such as PyTorch or TensorFlow. - Practical knowledge of supervised and unsupervised learning, model selection, benchmarking, error analysis and explain ability.
- Hands-on experience building and deploying generative AI or agentic AI solutions using LLMs, retrieval-augmented generation, embeddings, vector search, tool calling, prompt management, multi-step orchestration using LangGraph and MCP - Experience designing production data/ML pipelines and services using technologies such as SQL, Spark, Airflow, Databricks, REST APIs, Git, Docker and CI/CD. - Fluency in data strategy, including authoritative-source selection, data-product thinking, target-state architecture, reuse, interoperability and business-value alignment.
- Strong working knowledge of data governance, including data ownership, classification, quality, privacy, access, retention, controls and issue remediation. - Exposure to modern data platforms and storage patterns such as Snowflake, Databricks, Delta Lake, Apache Iceberg, Parquet, JSON or Avro. - Experience working with relational and NoSQL stores, large and heterogeneous datasets, and structured and unstructured information.
- Exposure to modern data platforms and storage patterns such as Snowflake, Databricks, Delta Lake, Apache Iceberg, Parquet, JSON or Avro. - Experience working with relational and NoSQL stores, large and heterogeneous datasets, and structured and unstructured information. - Ability to operate effectively in a regulated environment with strong documentation, change management, validation, testing and audit-readiness expectations.

Your next step

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About the role

We file this job under Data Leadership, by the work the posting describes.

Data leaders run data teams or design how a company's data fits together. Managers hire, set priorities and answer for whether the data work pays off; architects choose the systems and the shape of the data.

Expect years of hands-on data work, experience leading people or projects, and the ability to explain tradeoffs to executives.

Unlike a senior engineer or analyst, most of a data leader's week goes to people, planning and decisions rather than building.

US government figures for computer and information systems managers

Median yearly pay, May 2025
$175,140
Expected change, 2025 to 2035
15.8% more jobsagainst 3.5% for all jobs

The government has no code for data leaders, so these figures are for the closest group, computer and information systems managers, which includes data processing and data operations managers.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 11-3021.

Job description

View original posting ↗

Job Description:

At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our clients, teammates, communities and shareholders every day. Being a Great Place to Work and providing a culture of caring is core to how we drive Responsible Growth. We are intentional about fostering an inclusive workplace where every teammate has the opportunity to succeed, build a career and contribute to our shared success. This includes attracting and developing exceptional talent, recognizing and rewarding performance, and supporting our teammates’ physical, emotional, and financial wellness through affordable, competitive and flexible benefits. We value the unique perspectives individuals bring from all backgrounds and career paths - whether shaped by military service, community college education, or a wide range of work and life experiences. These journeys foster resilience, leadership and innovation, strengthening our workforce and positively impact the communities we serve. Bank of America is committed to an in-office culture that supports collaboration, engagement, and career development. Our approach includes clear in-office expectations, while providing an appropriate level of flexibility based on role-specific responsibilities and business needs. At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us!


Job Description:

Under the GRM Data Strategy & Management leadership team, the Data Analyst / AI Engineer will design, build and operationalize quantitative models and agentic AI solutions for complex risk and data-management use cases. This is a hands-on role for an experienced practitioner who can move from problem framing and data discovery through experimentation, production deployment, monitoring and continuous improvement. The role will partner with risk subject-matter experts, data owners, technology teams and governance partners to deliver explainable, scalable and controlled solutions in a highly regulated environment.

The successful candidate will combine strong Python and data engineering skills with basic understanding of data strategy, data lineage, metadata, data quality and data governance. The candidate should be able to translate business and control objectives into production-grade data and AI products, while documenting data provenance, model behavior, decisions and human oversight.


Responsibilities:

  • Build agentic AI solutions that use large language models, retrieval-augmented generation, tools, APIs and workflow orchestration to support research, analysis, decision support and operational processes.
  • Develop robust Python services, reusable libraries, data pipelines and APIs that integrate structured and unstructured data from multiple Systems of Record.
  • Create evaluation frameworks for ML and generative AI solutions, including accuracy, precision/recall, robustness, latency, cost, hallucination, groundedness and task-completion measures.
  • Implement appropriate human-in-the-loop controls, guardrails, audit trails, access controls, fallback paths and approval checkpoints for agentic workflows.
  • Partner with business and risk stakeholders to frame problems, define measurable success criteria and translate prototypes into scalable, production-grade capabilities.
  • Apply data strategy principles to identify authoritative sources, promote reuse, minimize redundant sourcing and align solutions to target-state data architecture.
  • Document and maintain end-to-end data lineage from source systems through transformations, features, models, prompts, agent actions and downstream outputs.
  • Embed data governance requirements into solution design, including metadata, ownership, classifications, quality controls, retention, privacy, entitlements and issue management.
  • Perform data discovery, profiling, quality assessment and root-cause analysis across large, complex datasets; establish controls and metrics to monitor data health.
  • Collaborate in cross-functional Agile delivery teams and communicate technical concepts, trade-offs, risks and outcomes clearly to both technical and executive audiences.
  • Mentor team members, contribute reusable patterns and standards, and help advance engineering discipline across GRM data and AI initiatives.

Required Skills:

  • Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Engineering, Statistics, Mathematics or a related quantitative discipline.
  • 5+ years of professional experience building data analytics, machine learning or AI solutions, with demonstrated ownership of solutions beyond experimentation and into production.
  • Advanced hands-on Python development, including clean, testable and modular code; experience with pandas, NumPy, scikit-learn and at least one deep-learning framework such as PyTorch or TensorFlow.
  • Practical knowledge of supervised and unsupervised learning, model selection, benchmarking, error analysis and explain ability.
  • Hands-on experience building and deploying generative AI or agentic AI solutions using LLMs, retrieval-augmented generation, embeddings, vector search, tool calling, prompt management, multi-step orchestration using LangGraph and MCP
  • Experience designing production data/ML pipelines and services using technologies such as SQL, Spark, Airflow, Databricks, REST APIs, Git, Docker and CI/CD.
  • Fluency in data strategy, including authoritative-source selection, data-product thinking, target-state architecture, reuse, interoperability and business-value alignment.
  • Strong working knowledge of data lineage and metadata management, including the ability to trace data from origin through transformations and consumption, identify controls and document dependencies.
  • Strong working knowledge of data governance, including data ownership, classification, quality, privacy, access, retention, controls and issue remediation.
  • Exposure to modern data platforms and storage patterns such as Snowflake, Databricks, Delta Lake, Apache Iceberg, Parquet, JSON or Avro.
  • Experience working with relational and NoSQL stores, large and heterogeneous datasets, and structured and unstructured information.
  • Ability to operate effectively in a regulated environment with strong documentation, change management, validation, testing and audit-readiness expectations.
  • Exceptional written, verbal and visual communication skills, with the ability to explain complex technical topics and influence stakeholders at multiple levels.

What Success Looks Like:

  • Delivers measurable improvements in analyst capacity, decision quality, risk coverage, cycle time or control effectiveness.
  • Moves viable use cases from prototype to sustainable model with clear ownership and controls
  • Creates reusable data, ML and agentic AI components that can be adopted across GRM rather than built as one-off solutions.
  • Improves transparency and trust through documented lineage, governance, explain ability and evidence-based performance metrics.

Skills:

  • Critical Thinking
  • Data Governance
  • Negotiation
  • Risk Management
  • Stakeholder Management
  • Attention to Detail
  • Change Management
  • Issue Management
  • Presentation Skills
  • Regulatory Relations
  • Business Acumen
  • Continuous Improvement
  • Controls Management
  • Data Management
  • Performance Management

Shift:

1st shift (United States of America)

Hours Per Week: 

40

Pay Transparency details

US - NJ - Jersey City - 525 Washington Blvd (NJ2525)

Pay and benefits information

Pay range

$109,100.00 - $203,500.00 annualized salary, offers to be determined based on experience, education and skill set.

Discretionary incentive eligible

This role is eligible to participate in the annual discretionary plan. Employees are eligible for an annual discretionary award based on their overall individual performance results and behaviors, the performance and contributions of their line of business and/or group; and the overall success of the Company.

Benefits

This role is currently benefits eligible. We provide industry-leading benefits, access to paid time off, resources and support to our employees so they can make a genuine impact and contribute to the sustainable growth of our business and the communities we serve.
Source details

View original posting ↗

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Pay
Pay range $109,100.00 - $203,500.00 annualized salary, offers to be determined based on experience, education and skill set. Discretionary incentive eligible
Location & working pattern

Jersey City

Working pattern and location restrictions need checking in the full posting.

Work authorization

No clear work-authorization passage found. Eligibility is unconfirmed.

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