Team Leader - Annotations Operations and Governance

Bloomberg; New York (NY); On-site; USD 150,000 - 210,000; Full time

Job summary

Bloomberg is seeking a Team Lead to own and scale the company’s annotation function across AI and data initiatives. The role oversees annotation operations and governance, applying standards at scale through SME-driven workflows, vendor execution, and strong operational controls.

The ideal candidate is technically grounded, systems-oriented, and comfortable operating at scale with rigorous judgment, calibration, and drift detection to improve data quality and model outcomes.

Qualifications

• Proven experience leading operational or program-focused teams.
• Strong technical judgment in designing or operating annotation systems for ML training/evaluation.
• Deep understanding of annotation systems, calibration, and drift detection.
• Experience running large-scale annotation or data operations with vendors and SMEs.
• Ability to enforce standards at scale while maintaining consistency.
• Excellent cross-functional leadership and comfort with ambiguity.
• Measurable program leadership with focus on outcomes and improvement.

Responsibilities

• Lead and develop a team operating and governing Bloomberg’s AI data annotation capability with high-quality output.
• Own annotation operations end-to-end, translating schemas into scalable workflows with measurable quality.
• Establish governance and quality mechanisms, including calibration, agreement analysis, and drift detection.
• Partner with AI, Data, and Platform teams to align outputs with production needs and model requirements.
• Ensure operational strength at scale, including workforce strategy, vendor oversight, and capacity planning.
• Drive continuous improvement through metrics, feedback loops, and root-cause analysis.
• Maintain judgment integrity as models and domains evolve.

Skills

People leadership

Technical judgment

Annotation systems

Quality methodologies

Vendor management

Cross-functional leadership

Program management

Education

Bachelor’s or Master’s degree in a relevant field

Tools

Annotation platforms

QA tooling

Data instrumentation

Job description

Bloomberg runs on data. Our products are fueled by powerful information. We combine data and context to paint the whole picture for our clients, around the clock – from around the world. In Data, we are responsible for delivering this data, news and analytics through innovative technology - quickly and accurately. We apply problem-solving skills to identify innovative workflow efficiencies, and we implement technology solutions to enhance our systems, products and processes - all while providing customer support to our clients.

Our team:

The Bloomberg Data AI group brings innovative AI technologies into Bloomberg’s Data organization while contributing deep financial domain expertise to the development of AI-powered products. We partner closely with stakeholders to align AI innovation with Bloomberg’s strategic objectives, focusing on optimizing data workflows and elevating the quality, intelligence, and usability of the data that drives our products. Our work amplifies the impact of the Data organization by delivering intelligent data solutions and domain-informed systems that enhance the capabilities and competitiveness of Bloomberg’s offerings.

What’s the role?

We are seeking a Team Lead to own and scale Bloomberg’s annotation function across AI and data initiatives, with responsibility for Annotation Operations and Annotation Standards & Governance. This role leads two tightly coupled but distinct capabilities: (1) governing canonical annotation standards and judgment frameworks, and (2) applying those standards at scale through operational execution, quality control, and continuous improvement.

The Team Lead will operate annotation as a shared service across our Data AI teams. They will ensure that centrally defined standards: schemas, labels, ambiguity frameworks, and calibration rules, are consistently and correctly applied in production through SME-driven workflows, vendor execution, and robust operational controls.

The ideal candidate is a technically grounded, systems-oriented leader who understands how annotated data shapes AI model behavior and evaluation outcomes. You are comfortable operating at scale while exercising strong technical judgment, enforcing standards, interpreting ambiguity, and using metrics to detect drift, diagnose failure modes, and continuously improve data quality.

In this role, you will help build a durable, repeatable annotation capability that produces correct, consistent, and reproducible data over time, supporting training, evaluation, monitoring, and production AI systems.

We’ll trust you to:

• Lead and develop a team responsible for operating and governing Bloomberg’s AI data annotation capability, delivering consistent, high-quality data through strong technical judgment and clear standards.
• Own annotation operations end-to-end, translating schemas and judgment frameworks into scalable workflows with measurable quality.
• Establish governance and quality mechanisms, including calibration, agreement analysis, and drift detection, that ensure consistent interpretation of standards.
• Partner closely with AI, Data, and Platform teams to align annotation outputs with production needs and downstream model requirements.
• Ensure operational strength at scale, including workforce strategy, vendor oversight, capacity planning, and service reliability.
• Drive continuous improvement through metrics, feedback loops, and root-cause analysis.
• Act as steward of judgment integrity, maintaining high agreement and durable decision-making frameworks as models and domains evolve.

You’ll need to have:

• Prior people leadership experience, including leading operational or program-focused teams.
• Demonstrated technical judgment in designing or operating annotation systems that support machine learning training, evaluation, or model assessment.
• Strong understanding of annotation systems and quality methodologies, including calibration, agreement modeling, and drift detection.
• Proven experience running large-scale annotation or data operations with vendor and SME workforces.
• Ability to enforce centrally defined standards while maintaining consistency at scale.
• Excellent cross-functional leadership skills and comfort operating in ambiguity-rich environments.
• Strong program leadership capability, with a focus on measurable outcomes and continuous improvement.
• Bachelor’s or Master’s degree in a relevant field, or equivalent practical experience.

We’d love to see:

• Experience supporting ML training, evaluation, or monitoring pipelines.
• Familiarity with annotation platforms, QA tooling, and data instrumentation.