Team Leader Annotations Operations and Governance

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 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 Bloombergs 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 Bloombergs 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 Bloombergs offerings.

Whats the role

We are seeking a Team Lead to own and scale Bloombergs 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.

Well trust you to:

• Lead and develop a team responsible for operating and governing Bloombergs 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.

Youll 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.

• Bachelors or Masters degree in a relevant field or equivalent practical experience.

Wed love to see:

• Experience supporting ML training evaluation or monitoring pipelines.

• Familiarity with annotation platforms QA tooling and data instrumentation.