Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Senior Data Annotation Analyst – Dialogue Labeling and Annotation Management

Bloomberg
London
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist

Senior Data Scientist - Growth London

Senior Machine Learning Engineer, Data for Embodied AI

Senior Machine Learning Engineer, Data for Embodied AI

Senior Machine Learning Engineer - Applied ML, Generative AI

Senior Machine Learning Engineer (Applied ML / Generative AI)

Senior Data Annotation Analyst – Dialogue Labeling and Annotation Management

London

Posted Jul 2, 2024 - Requisition No. 126289

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 optimize the value of our data by combining our domain and technical expertise to make our data fit-for-purpose, timely and accurate. We apply our problem-solving skills to identify innovative workflow efficiencies, and we implement technology solutions to better handle our data.

The Role:

As a Senior Data Annotation Analyst on our Dialogue Labeling and Annotation Management team (DLAM), you will be responsible for project coordination, prioritization, mentorship, coaching, and execution of strategic business objectives. Your key partners will be our AI Community Engineering teams and our Core Product team within Community. You will be the foundation of the DLAM team and will help support the development of machine learning models and AI technology, such as, AI assistance with security detection, transcription of voice data, classification, and more. We’ll trust you to become a product owner and understand the downstream usage of our data and use that knowledge to advise potential annotation changes. As a data annotation specialist, you will also be responsible for annotation efforts by in house contract workers. You will develop deep domain expertise in text annotation of financial instruments and will perform quality evaluation of annotation results produced by yourself and contract workers. This role will require you to collaborate across data teams as your team will serve as a resource for outside teams that require expertise and training in annotation management. Doing so will require critical thinking and collaboration across Data, Product, and Engineering teams.

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.

Bachelor's degree in Finance, Economics, Linguistics. or relevant degree/equivalent experience 4+ years of data management experience, for example improving data quality, accuracy, efficiency, or timeliness* Demonstrated project, work experience, or coursework that shows your interest and knowledge in the financial markets or human in the loop workflows Demonstrated interest or experience with data analysis Excellent written, communication, and presentation skills Strong organizational skills with the ability to balance multiple projects simultaneously A high-level proficiency with business intelligence/data visualization tools, preferably QlikSense Strong desire to structure and systemize processes, and motivation to push both existing and new workflows in that direction

We’d love to see:

Experience working with annotation schemas, edge cases, guideline development and maintenance, and semantic analysis Experience transforming workflows into a more timely and efficient process Experience working with human in the loop workflows Experience using native language skills to capture various forms of linguistic utterances with high accuracy Experience with one or more of the following asset classes: Fixed Income, Equities, and Foreign Exchange products

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!

Bloomberg is an equal opportunity employer and we value diversity at our company. We do not discriminate on the basis of 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, sexual and other reproductive health decisions, parental or caring status, physical or mental disability, pregnancy or parental leave, protected veteran status, status as a victim of domestic violence, or any other classification protected by applicable law.

Bloomberg provides reasonable adjustment/accommodation to qualified individuals with disabilities. Please tell us if you require a reasonable adjustment/accommodation to apply for a job or to perform your 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, using a sign language interpreter, or using specialized equipment.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How to Write an AI CV that Beats ATS (UK examples)

Writing an AI CV for the UK market is about clarity, credibility, and alignment. Recruiters spend seconds scanning the top third of your CV, while Applicant Tracking Systems (ATS) check for relevant skills & recent impact. Your goal is to make both happy without gimmicks: plain structure, sharp evidence, and links that prove you can ship to production. This guide shows you exactly how to do that. You’ll get a clean CV anatomy, a phrase bank for measurable bullets, GitHub & portfolio tips, and three copy-ready UK examples (junior, mid, research). Paste the structure, replace the details, and tailor to each job ad.

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.

Why AI Careers in the UK Are Becoming More Multidisciplinary

Artificial intelligence is no longer a single-discipline pursuit. In the UK, employers increasingly want talent that can code and communicate, model and manage risk, experiment and empathise. That shift is reshaping job descriptions, training pathways & career progression. AI is touching regulated sectors, sensitive user journeys & public services — so the work now sits at the crossroads of computer science, law, ethics, psychology, linguistics & design. This isn’t a buzzword-driven change. It’s happening because real systems are deployed in the wild where people have rights, needs, habits & constraints. As models move from lab demos to products that diagnose, advise, detect fraud, personalise education or generate media, teams must align performance with accountability, safety & usability. The UK’s maturing AI ecosystem — from startups to FTSE 100s, consultancies, the public sector & universities — is responding by hiring multidisciplinary teams who can anticipate social impact as confidently as they ship features. Below, we unpack the forces behind this change, spotlight five disciplines now fused with AI roles, show what it means for UK job-seekers & employers, and map practical steps to future-proof your CV.