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: 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. By investing in AI at a strategic level, we expand our practice of engaging with AI to one that is embedded across Data. We encourage our internal processes to take advantage of new AI technologies and strengthen Data's role in providing robust domain expertise and influential data artifacts to Bloomberg's products. This way, our clients will continue to have high quality data and access to new types of datasets. What's the Role? A Senior Data Management Professional (DMP) is a key role within our organization responsible for providing domain expertise in both financial concepts and annotation program management, to the development of our AI products. These individuals act as proactive technical leaders by setting the framework in achieving quality and consistency in the evaluation and training datasets for models that power our AI-enhanced products, and delivering scalable governance in annotation program management across Bloomberg Data. Beyond governing data processes and being problem solvers, they are expected to transform the responsibilities of the team and scale the impact beyond what's possible today. The role in the Data AI Annotation team covers all annotation program components in developing the evaluation and training of AI models at Bloomberg. Being responsible for the quality of the annotated data, and product quality will be a crucial part of the role, with key work spanning ownership around consensus management, adjudication, and instruction and task design. The team is a critical partner in ensuring the stability and growth of the company which relies on bringing new technology to customers with increased interests in Artificial Intelligence. We'll trust you to: Create strategies to analyze processes and data quality questions to ensure our datasets are fit-for-purpose. Safeguard the creation of high-quality training data for generative AI models in collaboration with the annotation project manager. Leverage data annotation tools and platforms, including labeling software and data management systems to ensure quality. Apply domain expertise to inform annotation decisions and ensure high-quality outputs. Review and further enhance annotation guidelines, and promote the development of standard processes in data annotation. Rely upon data analysis skills to identify trends, patterns, and anomalies, and make informed decisions on annotation approaches. Lead on problem-solving to resolve complex annotation challenges and ensure data quality. Stay up-to-date with industry trends and standard methodologies in data annotation and finance/news. Be ready to take a hands-on role in project and product coordination when needed- with input from Technical specialist, Annotation manager and Senior annotators. You'll need to have: *Please note we use years of experience as a guide, but we certainly will consider applications from all candidates who are able to demonstrate the skills necessary for the role. A bachelor's degree or above in Statistics, Data Analytics and Data Science or other STEM related fields. A minimum of four years of demonstrated experience in data management concepts such as data quality, random sampling and data modeling. Past project/experience owning financial datasets or proven past experience working on financial market concepts. Demonstrable experience in Data Profiling/Analysis using tools such as Python, R, or SQL. Extensive experience in communicating results in a clear, concise manner using data visualization tools. Demonstrated ability taking a logical approach and applying critical thinking skills in order to solve problems. We'd Love to See: DAMA CDMP or DCAM certifications. Keen interest and familiarity with generative AI frameworks. Understanding of the importance of high quality annotations. Experience in using Bloomberg Data, Bloomberg Terminal, and/or enterprise financial data products. Interest in solving problems and developing data-driven methodologies for high precision& high recall anomaly detection. Past project experience using the Agile/Scrum project management methodology. Does this sound like you? Apply if you think we're a good match. We'll get in touch to let you know next steps!