Senior Data Management Professional - Data Product Owner (Data AI)
Used Tools & Technologies
NLP GenAIRequired Skills & Competences
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.
Python @ 4
SQL @ 4
R @ 4
Tableau @ 4
Leadership @ 4
Data Engineering @ 4
HTML @ 4
JavaScript @ 4
Agile @ 4
Generative AI @ 4
AI @ 4
Data Visualization @ 4
Data Modeling @ 4
Profiling @ 4
Agentic AI @ 3
- 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 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 workflow efficiencies and implement technology solutions to enhance our systems, products, and processes.
Team
Data AI contributes to the building of Bloomberg’s AI-enhanced products at scale by curating model training data and enhancing how our internal processes use AI. We provide evaluation and annotation frameworks connecting natural language processing and human judgment in order to elevate the quality, intelligence, and usability of the data that drives our products. By investing in AI at a strategic level, we expand our practice of engaging with AI to one that is embedded across Data and provide robust domain expertise and influential data artifacts to Bloomberg’s products.
Role overview
The Data Product Owner serves as the strategic leader responsible for transforming business operations through data and AI. By aligning product, engineering, and operational partners around a shared vision, they define and deliver the data capabilities that enable intelligent automation, operational scale, and continuous improvement. The role shapes how the organization uses data as a strategic asset through workflow optimization, process simplification, and thoughtful application of AI to increase efficiency, improve quality, and create sustainable business value.
Responsibilities
- Own and evolve scalable frameworks and strategies for instruction and evaluation task design to ensure datasets remain fit-for-purpose for complex generative AI behaviors.
- Align data frameworks and evaluation strategies with product objectives to guarantee trustworthy, consumable intelligence that supports actionable user decisions.
- Act as the primary multi-functional liaison, driving alignment between Product, Engineering, and Data teams and translating technical complexities into actionable insights.
- Partner with cross-functional teams to define product-aligned requirements and reusable evaluation rubrics, ensuring outcomes meet rigorous Data Quality standards.
- Drive strategic evolution of evaluation infrastructure by pioneering reusable, automated frameworks that accelerate multi-functional product delivery.
Requirements
- Bachelor’s degree or equivalent experience in Finance, Business, Economics, Accounting, STEM or equivalent qualifications.
- Minimum of four years of demonstrated experience in data management concepts, including data quality, modeling, and random sampling.
- Extensive experience using data visualization tools such as Tableau or Qlik Sense to communicate sophisticated results.
- Demonstrable experience in data profiling/analysis using tools such as Python, R, or SQL.
- Past project/experience analyzing financial datasets or demonstrable experience working on financial market concepts.
- Logical approach to problem-solving with ability to resolve complex annotation and data-architectural challenges.
- Keen interest in and familiarity with generative AI frameworks and the requirements of Agentic AI.
- Excellent stakeholder management and project leadership skills, with ability to evaluate design trade-offs and translate technical complexities between Engineering, Product, and Data teams.
- Experience in data management concepts such as data quality, data modeling, and data engineering.
Preferred / Nice-to-have
- DAMA CDMP or DCAM certifications.
- Experience using Bloomberg Data, Bloomberg Terminal, and/or enterprise financial data products.
- Interest in developing data-driven methodologies for high precision & high recall anomaly detection.
- Past project experience using Agile/Scrum methodologies to manage complex data lifecycles.
- Experience customizing or developing annotation interfaces using Javascript or HTML.
Compensation & Benefits
Salary Range: 110,000 - 190,000 USD Annual (+ Benefits + Bonus)
The referenced salary range is based on the Company's good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training and skill level.
Bloomberg offers a comprehensive benefits plan that may include merit increases, incentive compensation (exempt roles only), paid holidays, paid time off, medical, dental, vision, short and long term disability benefits, 401(k) with match, life insurance, and various wellness programs. The Company does not provide benefits directly to contingent workers/contractors and interns.