Minimum 1 year of relevant experience., Proficiency in English at B2 or higher (preferably C1)., Strong analytical skills and understanding of business workflows., Attention to detail and ability to create clear annotation guidelines..
Key responsibilities:
Develop and implement data annotation guidelines.
Review and validate labeled data, providing feedback.
Collaborate with data scientists and ML engineers on dataset creation.
Manage annotation workflows and ensure data quality and compliance.
Report this Job
Help us maintain the quality of our job listings. If you find any issues
with this job post, please let us know. Select the reason you're reporting
this job:
Provectus is an Artificial Intelligence consultancy and solutions provider, helping businesses achieve their objectives through AI.
We are recognized by industry think tanks as a leading provider of AI solutions in specific business domains, driven by sophisticated IT service management and tech innovation. Provectus is a value driver and a trusted partner for our clients and employees.
Provectus is an AWS Premier Consulting Partner with competencies in Data & Analytics, DevOps, and Machine Learning. We design and build AI solutions for industry-specific use cases, Data and Machine Learning foundation, Cloud transformation, and DevOps adoption.
As a Business Analyst & Data Annotator, you will play a crucial role in gathering and analyzing business requirements, acting as a bridge between stakeholder needs and technical teams. You will also handle the data annotation process, ensuring the production of high-quality, accurately labeled datasets necessary for training machine learning models.
This role involves close collaboration with ML engineers, data scientists, and business teams to ensure that data aligns with project goals. Your work will center on translating complex business needs and technical specifications into clear instructions, managing data labeling workflows, and maintaining data quality standards.
Responsibilities:
Develop and implement detailed guidelines and instructions for data labeling and annotation to ensure consistency and accuracy across datasets;
Review and validate labeled data, providing constructive feedback to annotation teams to improve data quality and adherence to project standards;
Collaborate with data scientists and ML engineers to prepare, organize, and support the creation of high-quality annotated datasets for model training;
Manage the annotation workflow, prioritize tasks, and track progress to ensure timely delivery of labeled data;
Maintain high standards of data privacy, security, and compliance throughout all annotation processes;
Gather and analyze business requirements, workflows, and terminology to understand data needs and improve annotation processes;
Facilitate communication between technical teams and stakeholders by translating complex technical or domain-specific language into clear, accessible instructions and explanations;
Offer insights into business processes that could benefit from automation or ML solutions, supporting the design and implementation of such projects;
Support continuous improvement of data annotation guidelines, workflows, and overall business analysis practices to enhance efficiency and data quality.
Requirements:
At least 1 year of experience in the relevant role;
Excellent English language skills (B2 level or higher, ideally C1), especially when working with reports containing complex terminology;
Strong analytical skills and an understanding of business workflows;
Attention to detail and ability to create clear instructions and guidelines for annotation teams;
Understanding of data privacy, security standards, and compliance requirements.
Nice to Have:
Basic knowledge of machine learning concepts and data management principles;
Familiarity with ML workflows, data pipelines, and MLOps tools;
Experience with cloud platforms such as AWS, GCP, or Azure;
Experience with data labeling or annotation;
Experience in creating markups for AI;
Insurance industry background.
Required profile
Experience
Level of experience:Entry-level / graduate
Industry :
Information Technology & Services
Spoken language(s):
English
Check out the description to know which languages are mandatory.