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Finance Data Annotation Quality Analyst
Paris, Ile-de-France, France
Actively hiring, first seen by us today- Pay
- Pay not listed
- Work setting
HybridLocation limits apply — work setting source
Role Summary We’re seeking highly motivated Data Quality Analysts with strong analytical skills and a keen eye for detail to join our Human Data Annotation team within the Science organisation. This is a hybrid quality reviewing and tooling role: you'll spend the majority of your time reviewing and auditing Finance (any subdomain) annotations against rubrics to ensure data used for training and evaluating AI models meets the highest standards of quality and efficiency.
Work setup in the employer’s posting: Hybrid
From the employer’s posting- Employment
Full-time — employment source
Employment type in the employer’s posting: FullTime
From the employer’s posting
What you’ll work on
Full postingWe’re seeking highly motivated Data Quality Analysts with strong analytical skills and a keen eye for detail to join our Human Data Annotation team within the Science organisation.
you'll spend the majority of your time reviewing and auditing Finance (any subdomain) annotations against rubrics to ensure data used for training and evaluating AI models meets the highest standards of quality and efficiency.
What you’ll bring
All qualificationsCore experience
- Excellent communication, interpersonal, and organisational abilities
- Familiarity with rubric-based evaluation concepts, inter-annotator agreement, or quality measurement for human-labeled data
- Experience building an annotation team through interviews and training
- Proficient in at least one programming language (e.g.
- Prior experience in data annotation for AI/ML, especially LLM training (SFT, RLHF, preference data), evals/benchmarks, or agentic data
Qualification wording
Excellent communication, interpersonal, and organisational abilities
Familiarity with rubric-based evaluation concepts, inter-annotator agreement, or quality measurement for human-labeled data
Experience building an annotation team through interviews and training
Proficient in at least one programming language (e.g. Python)
Prior experience in data annotation for AI/ML, especially LLM training (SFT, RLHF, preference data), evals/benchmarks, or agentic data
Benefits in the posting
Full benefits wording- We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks.
- Privacy Policy
From the employer’s posting.
About mistral.ai
Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute.
In the employer’s words · Read in context
Posting record
Report an errorActively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Nov 9, 2026today
- Recorded sightings
- 1
- Employer says posted
- Oct 15, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
mistral.ai is hiring
18 open jobs
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- Python
Where the posting names them
- Experience building an annotation team through interviews and training - Proficient in at least one programming language (e.g. Python) - Prior experience in data annotation for AI/ML, especially LLM training (SFT, RLHF, preference data), evals/benchmarks, or agentic data
Your next step
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About the role
We file this job under Analyst, by the work the posting describes.
Analysts answer business questions with data. They pull numbers with SQL, build reports and dashboards, and explain what changed and why to the people making decisions.
Most postings ask for SQL, spreadsheets, a dashboard tool such as Tableau or Power BI, and clear writing.
Unlike a data scientist, an analyst mostly explains what happened rather than building models that predict what will.
Job description
About Mistral
Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms.
We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited.
Role Summary
We’re seeking highly motivated Data Quality Analysts with strong analytical skills and a keen eye for detail to join our Human Data Annotation team within the Science organisation. This is a hybrid quality reviewing and tooling role:
you'll spend the majority of your time reviewing and auditing Finance (any subdomain) annotations against rubrics to ensure data used for training and evaluating AI models meets the highest standards of quality and efficiency.
and the remainder building, maintaining, and troubleshooting annotation operations.
You'll collaborate closely with the annotators, technical program manager, and science stakeholders, and contribute to refining the guidelines and processes that shape how our data is produced.
Key Responsibilities
In collaboration with the technical team, review/audit annotations, clarify requirements, share insights, surface systemic issues, edge cases, and gaps in guidelines, to improve annotation processes and guidelines.
Generate and validate high-quality finance-oriented data annotations yourself when needed, based on guidelines and continuous feedback, for the development and evaluation of AI models
Build and maintain internal tools and automation that streamline annotation or review workflows such as visualization dashboards, batch configuration scripts, output management utilities, and similar
Troubleshoot campaign issues (e.g. tooling, guidelines) for annotators
Organise annotator training and coordinate feedback between annotators and reviewers.
About you
A degree (minimum Masters level) in a Finance discipline.
At least 3 years of professional experience in the Financial domain.
Outstanding analytical and research skills
Some familiarity with programming languages, with the ability to read standard output formats such as .jsonl files.
Exercises great judgement with complex instructions, limited data, and/or multiple information sources and ability to surface edge cases, ambiguities, or gaps in guidelines accordingly.
Excellent communication, interpersonal, and organisational abilities
Adapts easily to dynamic environments and changing requirements
Appetite for operational work and high tolerance for repetitive tasks with a sustained focus and accuracy on detail-oriented, high-volume review work.
Professional proficiency in English, with strong writing and comprehension skills
Nice to have
Familiarity with rubric-based evaluation concepts, inter-annotator agreement, or quality measurement for human-labeled data
Experience building an annotation team through interviews and training
Proficient in at least one programming language (e.g. Python)
Prior experience in data annotation for AI/ML, especially LLM training (SFT, RLHF, preference data), evals/benchmarks, or agentic data
Comfortable working in a Unix-like terminal and using git workflows (branches, merges, resolving conflicts)
What We Offer
We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks.
For the most up-to-date details on benefits available in your location, please refer to our Benefits page.
Privacy Policy
Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Paris, Ile-de-France, France
Role Summary We’re seeking highly motivated Data Quality Analysts with strong analytical skills and a keen eye for detail to join our Human Data Annotation team within the Science organisation. This is a hybrid quality reviewing and tooling role: - you'll spend the majority of your time reviewing and auditing Finance (any subdomain) annotations against rubrics to ensure data used for training and evaluating AI models meets the highest standards of quality and efficiency.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.