Senior Data Management Professional - Data Engineering

Senior Data Management Professional - Data Engineering

Location
London

Business Area
Data

Ref #
10044247

Description & Requirements

Bloomberg runs on data. Our products are fueled by powerful information. Webine 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 supplying deep financial domain expertise to the development of AI-powered products. We partner closely with team members 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 improve the capabilities andpetitiveness of Bloomberg's offerings.
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 scalableernance in annotation program management across Bloomberg Data. Beyonderning 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 programponents 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 thepany which relies on bringing new technology to customers with increased interests in Artificial Intelligence.
We'll trust you to:

Build strategies to analyze processes and data engineering 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 coordinator.
Collaborate on database schema design and configure ETL pipelines to onboard new data sets.
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 improve 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 sophisticated 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 demonstrable experience in data management concepts such as data engineering, data quality and data modeling.
Demonstrable experience in Data Profiling/Analysis/Engineering using tools such as SQL and Python or R.
Experience using data visualization tools such as Tableau, Qlik Sense or Splunk.
Past projects that involved owning financial datasets, or other demonstrable work with financial-market concepts.
Proficiency in discussing technical concepts and experience evaluating trade-offs in design with Engineering and Product.
Extensive experience inmunicating results in a clear, concise manner using data visualization tools.
Consistent track record in taking a logical approach and applying critical thinking skills in order to address 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.