Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 4
GenAI
Generative AI
Leadership @ 7
Machine Learning @ 6
Project Management @ 6
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Bloomberg's Data department delivers data, news, and analytics through innovative technology. The Data Artificial Intelligence group develops a strategic vision for incorporating AI within the department and promotes Data as a partner in developing AI-enhanced products across the firm.
As Team Leader of the Document Research team, you will lead the development of evaluation and annotation programs for AI applications and experiences in the document research space. You will represent Data in collaboration with CTO, Engineering, and Product teams, contributing domain expertise to the creation of evaluation and annotation programs. Your work will support expert research systems powered by generative AI across multiple domains.
The ideal candidate is a technically grounded, systems-oriented leader who understands how annotated data influences AI model behavior and evaluation outcomes. You should be comfortable operating at scale, applying technical judgment, enforcing standards, interpreting ambiguity, using metrics to detect drift, diagnosing failure modes, and continuously improving data quality.
Responsibilities
- Establish and maintain partnerships with Engineering, CTO, and Product counterparts.
- Contribute to priorities and implementation roadmaps for client-facing AI applications and experiences.
- Recruit, mentor, and develop a team of data management professionals specializing in evaluation frameworks, annotation management, and project management.
- Promote a culture of cross-team collaboration.
- Balance operational stability with the adoption of new technologies during implementation.
- Challenge existing assumptions and identify improvements to schemas, workflows, and operational processes.
- Participate in technical discussions and provide insights on design, code reviews, and other relevant areas.
- Collaborate with strategic partners on large-scale technical and operational programs with enterprise-wide influence.
- Support data governance, cross-team organization, and stakeholder engagement.
Requirements
- Bachelor's or master's degree.
- At least 3 years of experience leading operational or program-focused teams.
- Demonstrated technical judgment in designing or operating annotation systems supporting machine learning training, evaluation, or model assessment.
- Good understanding of annotation systems and quality methodologies, including calibration, agreement modeling, and drift detection.
- Experience managing large-scale annotation or data operations involving vendor and subject-matter-expert workforces.
- Ability to enforce centrally defined standards while maintaining consistency at scale.
- Excellent multifunctional leadership skills and comfort operating in ambiguous environments.
- Strong program leadership capabilities focused on measurable outcomes and continuous improvement.
Preferred Qualifications
- Exposure to the Bloomberg Terminal and/or Enterprise Data products.
- Current knowledge of financial markets and how Bloomberg products deliver value to users.
- Experience with the Data technology stack and HiTL platform, such as Gigwork, Autolab, and BBDS.
- Project Management Professional (PMP) certification or other relevant certifications.
Benefits
Benefits and total rewards may include merit increases, incentive compensation for exempt roles, paid holidays, paid time off, medical, dental, vision, short- and long-term disability benefits, 401(k) matching, life insurance, and wellness programs.