Data AI Trainer

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.

The Team

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. We also roll up our sleeves to create our own training and applied exercises. 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 use interactive technology, peer learning, and a highly collaborative team culture to ensure success for everyone. We encourage participation and provide opportunities for trainees to learn from each other and the professionals within Data.

We’ll Trust You To:

• 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
• Partner with engineers and domain experts to ensure we’re meeting client needs and leveraging the best technology solutions
• Develop self-service materials that enable teams to independently design experiments and adopt new tools
• Stay current with emerging experimentation methods, AI tools, and financial market dynamics, continuously refining curricula to meet evolving Data organization needs and business priorities.
• Commitment to cultivating a continuous learning culture across technical teams

You’ll Need To Have:

• 3+ years applied experience in applied AI solutions.
• Bachelor’s degree or higher in Computer Science, Engineering, Data Science, or other data-related field
• Experience mentoring or teaching technical material, with a passion for continuous learning and knowledge sharing. Ability to translate technical concepts into clear learning content and documentation.
• Strong communication and teaching abilities, a proven track record explaining complex quantitative concepts to both technical and non-technical audiences through clear examples and hands-on exercises
• 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
• Proven problem-solving skills and adaptability in evolving, fast-paced environments
• Collaborative approach to partnering across global teams and aligning with business priorities
• Effective project management skills to develop and manage a roadmap and deliver milestones in a timely manner.
• Ability to flexibly adapt to a changing environment
• Interest in financial market datasets and their application to data and AI solutions

We’d Love To See:

• Familiarity with modern data tools and frameworks (e.g., Airflow, Dagster, dbt, Spark, cloud data platforms)
• Certification in DAMA CDMP, EDM DCAM or similar
• 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

**Does this sound like you?**Apply if you think we're a good match. We'll get in touch to let you know what the next steps are.

If indicated, please note that years of experience are a guide; we will consider applications from all candidates who can demonstrate the skills necessary for the role. Discover what makes Bloomberg unique - watch our podcast series for an inside look at our culture, values, and the people behind our success.

Accommodations

Bloomberg provides reasonable adjustment/accommodation to individuals with disabilities. Please tell us if you require a reasonable adjustment/accommodation to apply for a job. Examples of reasonable adjustment/accommodation include but are not limited to making a change to the application process or work procedures, providing documents in an alternate format or using specialized equipment. To request an adjustment/accommodation to apply for a job, please email AMER_recruit@bloomberg.net (Americas), EMEA_recruit@bloomberg.net (Europe, the Middle East and Africa), or APAC_recruit@bloomberg.net (Asia-Pacific), based on the region you are submitting an application for. We may share your information with a third party provider of accommodations services who may use this information to reach out to you for the purposes of accommodating your application.

Equal Opportunity

Bloomberg is an equal opportunity employer and prohibits discrimination in employment. It is Bloomberg’s policy to provide equal opportunity and access for all persons, and the Company is committed to attracting, retaining, developing, and promoting the most qualified individuals without regard to age, ancestry, color, gender identity or expression, genetic predisposition or carrier status, marital status, national or ethnic origin, race, religion or belief, sex, sexual orientation, self-identified or perceived sex, sexual and other reproductive health decisions, parental or caring status, physical or mental disability, pregnancy, childbirth or related medical conditions, or parental leave, protected veteran status, status as a victim of domestic violence, or any other classification protected by applicable law (each, a “Protected Characteristic”). Bloomberg prohibits treating applicants or employees less favorably in connection with the terms and conditions of employment, in all phases of the employment process, because of one or more Protected Characteristics.