Data AI Trainer

2 days ago

London, United Kingdom Bloomberg Full time

Data
Bloomberg runs on data. We combine data and context to paint the whole picture for our clients, around the clock – from around the world. In the Data department, we are responsible for delivering this data, news, and analytics through innovative technology — quickly and accurately. At Bloomberg, our team is responsible for onboarding our junior data engineers, as well as providing learning opportunities to develop the skills of our nearly 2,000 Data employees. We collaborate with all teams across Data to ensure that we deliver the highest quality educational development. You can support our purpose by preparing Data teams with the confidence to apply AI tools into data processing workflows responsibly and effectively. The work we accomplish will contribute to AI products used by external Bloomberg clients.
We strive to make our curriculum exciting for both trainers and trainees; We encourage participation and provide opportunities for trainees to learn from each other and the professionals within Data.
Design and deliver training that enables teams to evaluate process changes - such as adopting new data pipelines, switching validation methods, or implementing AI-assisted workflows - and quantify their impact on dataset quality and business outcomes.
Create hands-on labs where teams design experiments on real Bloomberg datasets—testing pipeline changes, evaluating new tools, and measuring quality improvements
Explain core statistical concepts (sampling, correlation, causation, p-values) and AI/ML fundamentals (prompt engineering, model validation) in the context of data quality and process optimization.
Incorporate AI-assisted tools (e.g., GitHub Copilot, ChatGPT, NotebookLM) into training design and delivery.
Ensure teams maintain the highest standards for data quality, observability, and governance, alongside the implementation of transformative AI technologies.
Stay current with emerging experimentation methods, AI tools, and financial market dynamics—continuously refining curricula to meet evolving Data organization needs and business priorities.
3+ years applied experience in applied AI solutions.
~ Bachelor’s degree or higher in Computer Science, Engineering, Data Science, or other data-related field.
~ Ability to translate technical concepts into clear learning content and documentation.
~ Ability to identify learning needs through stakeholder consultation and translate them into scalable, practical training solutions
~ Understanding of data quality metrics (accuracy, completeness, timeliness) and concepts (data observability, governance) and how to assess them through statistical methods
~ Effective project management skills to develop and manage a roadmap and deliver milestones in a timely manner.
~ Interest in financial market datasets and their application to data and AI solutions.

Familiarity with modern data tools and frameworks (e.g., Airflow, Dagster, dbt, Spark, cloud data platforms)
Examples of technical content you've created—whether documentation, tutorials, presentations, or internal training materials
Hands-on experience with financial data, market data, or other business-critical datasets

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