Jobs in Mauritius
Computer Vision Annotator (Maurice)
Job Title: Computer Vision Annotator Location: Remote (Worldwide) Job Summary: The Computer Vision Annotator is responsible for accurately labeling and annotating image and video data to support the development and training of computer vision and machine learning models. This role plays a critical part in improving model performance by creating high-quality datasets used for object detection, image classification, segmentation, tracking, and other visual recognition tasks. Responsibilities • Perform high-precision annotation on visual data using specialized tools. Tasks include: • Drawing accurate bounding boxes, polygons, and polylines around objects of interest. • Placing key points for pose estimation or landmark detection. • Creating 3D cuboids and annotating point cloud data for spatial awareness applications (e.g., autonomous vehicles, robotics). • Conducting semantic/instance segmentation to label every pixel in an image. • Interpret complex labeling taxonomies and project specifications. Identify ambiguous cases and collaborate with project managers and data scientists to refine annotation guidelines for clarity and scalability. • Utilize advanced features of annotation tools such as CVAT, Label Studio, 3D Slicer, or Amazon SageMaker Ground Truth. Provide feedback to engineering teams to improve tool functionality and workflow efficiency. • Proactively identify challenging data patterns, edge cases, and potential biases in datasets. Escalate these findings to help improve model robustness and mitigate bias. • Contribute to the development of annotation best practices, workflow optimizations, and training materials for new annotators. • Assist in basic data preparation tasks such as resizing images, converting data formats, or ensuring sensor data synchronization (e.g., time-stamp alignment for video and LiDAR). • Assist in tracking key performance insights (KPIs) such as annotation throughput, precision, and recall. Participate in calibration sessions to ensure consistency across the team. Requirements • Minimum of 2 years of experience in data annotation, data labeling, or quality assurance specifically for computer vision or Machine Learning projects. • Demonstrated proficiency with a variety of annotation techniques including bounding boxes, polygons, key points, 3D cuboids, and segmentation masks. • Extensive hands-on experience with industry-standard annotation tools like CVAT, label Studio, 3D Slicer, Supervisely. • Solid understanding of computer vision concepts and terminology (e.g., object detection, image classification, LiDAR, point clouds). • Familiarity with quality control processes such as consensus labeling, audit sampling, gold-task seeding, and inter-annotator agreement metrics. • Exceptional attention to detail with an unwavering commitment to accuracy and consistency. Proven ability to maintain high-quality output even when labeling repetitive tasks. • Strong written and verbal communication skills in English. Ability to document workflows clearly and collaborate effectively teams and clients.
Data Scientist
Who are we? Valuement is an international consulting company, part of Mantu Group, that focuses on business processes and data analysis. Its primary goal is to reveal and ensure long-term competitiveness for its clients. We are actively developing our markets and therefore we are looking for a Data Scientist to implement projects within our operational team in Mauritius. Successful candidates will have the opportunity to be part of an international, young and fast-growing group with real opportunities for professional development at all levels. We are looking for an enthusiastic, ambitious, and curious professional, able to think outside the box and with a strong interest for performing analyses and working with data. Job Description: As a member of the Data Factory team, under the responsibility of a Data Scientist, you will provide data services to internal clients. You will handle and analyze large datasets to create value for our clients’ data. Combining computer science, development, modeling, statistics, and analytics skills, you will help Valuement to develop its business. Your Missions: • Lead the data analysis lifecycle for clients: discover raw data, convert, enrich, design, analyze, and develop algorithms • Identify patterns and trends in data sets • Work closely with our Data & Business Analysis (DBA) team to understand business needs and collect requirements to ensure goal achievement • Report results back to your manager • Develop solutions for automating data analysis and deploy them across all countries • Ensure data quality before delivery to internal or external clients Your Profile: • Degree in Computer Science, Mathematics, Statistics, or Information Technology (a Master’s degree is mandatory, except in the case of a Bachelor’s degree specifically in Computer Science) • Expertise in data analysis • Experience with RDBMS (SQL Server, Oracle, MySQL, PostgreSQL) • Experience in SQL, including basic knowledge of SQL programming (T-SQL or PL-SQL) • Experience in development with R or Python is appreciated • English fluent. Additional languages are a plus. • Ability to analyze large and complex datasets • You demonstrate a strong analytical mindset and an inclination for problem-solving • You pay attention to detail, ensuring thorough and accurate work What we offer: • Hybrid work policies • Competitive compensation scheme (permanent contract + commissions and benefits) • Real possibility to grow fast into a management role • International environment, overseas projects to develop, and mobility opportunities Valuement is proud to be an equal-opportunity workplace. We are committed to promoting diversity within the workforce and creating an inclusive working environment. For this purpose, we welcome applications from all qualified candidates regardless of gender, sexual orientation, race, ethnicity, beliefs, age, marital status, disability, or other characteristics
Data Scientist - F/M/X
Job Description Who are we? Valuement is an international consulting company, part of Mantu Group, that focuses on business processes and data analysis. Its primary goal is to reveal and ensure long-term competitiveness for its clients. We are actively developing our markets and therefore we are looking for a Data Scientist to implement projects within our operational team in Mauritius. Successful candidates will have the opportunity to be part of an international, young and fast-growing group with real opportunities for professional development at all levels. We are looking for an enthusiastic, ambitious, and curious professional, able to think outside the box and with a strong interest for performing analyses and working with data. Job Description: As a member of the Data Factory team, under the responsibility of a Data Scientist, you will provide data services to internal clients. You will handle and analyze large datasets to create value for our clients’ data. Combining computer science, development, modeling, statistics, and analytics skills, you will help Valuement to develop its business. Your Missions: • Lead the data analysis lifecycle for clients: discover raw data, convert, enrich, design, analyze, and develop algorithms • Identify patterns and trends in data sets • Work closely with our Data & Business Analysis (DBA) team to understand business needs and collect requirements to ensure goal achievement • Report results back to your manager • Develop solutions for automating data analysis and deploy them across all countries • Ensure data quality before delivery to internal or external clients Your Profile: • Degree in Computer Science, Mathematics, Statistics, or Information Technology (a Master’s degree is mandatory, except in the case of a Bachelor’s degree specifically in Computer Science) • Expertise in data analysis • Experience with RDBMS (SQL Server, Oracle, MySQL, PostgreSQL) • Experience in SQL, including basic knowledge of SQL programming (T-SQL or PL-SQL) • Experience in development with R or Python is appreciated • English fluent. Additional languages are a plus. • Ability to analyze large and complex datasets • You demonstrate a strong analytical mindset and an inclination for problem-solving • You pay attention to detail, ensuring thorough and accurate work What we offer: • Hybrid work policies • Competitive compensation scheme (permanent contract + commissions and benefits) • Real possibility to grow fast into a management role • International environment, overseas projects to develop, and mobility opportunities Valuement is proud to be an equal-opportunity workplace. We are committed to promoting diversity within the workforce and creating an inclusive working environment. For this purpose, we welcome applications from all qualified candidates regardless of gender, sexual orientation, race, ethnicity, beliefs, age, marital status, disability, or other characteristics
Computational Linguist Annotator (Maurice)
JOB TITTLE : Computational linguist Annotator LOCATION: Remote (Worldwide) EMPLOYMENT TYPE: Full Time JOB SUMMARY We are seeking a highly motivated Computational Linguist with strong expertise in linguistic annotation and natural language processing (NLP). In this role, you will design, implement, and evaluate annotation frameworks that support the development of advanced AI language systems. You will work closely with machine learning engineers, data scientists, and annotation teams to ensure high-quality linguistic datasets. Key Responsibilities • Design linguistic annotation schemas for complex NLP tasks including semantic role labeling, discourse parsing, coreference resolution and multimodal language. • Develop comprehensive annotation guidelines that balance linguistic precision with annotator usability and scalability. • Collaborate with new product teams to translate business requirements into linguistic annotation frameworks. • Ensure schemas capture relevant linguistic phenomena while remaining computationally tractable. • Build and maintain annotation interfaces, quality assurance dashboards and data management tools. • Develop scripts and utilities for data preprocessing, validation and analysis. Requirements • Bachelor's degree in Linguistics, English or a relating field. • Minimum 5 years’ experience in computational linguistics, language annotation, or NLP data operations. • Strong academic foundation in syntax, semantics, pragmatics and discourse analysis. • Experience in building and customizing annotation tools and work flows. • Track record in managing annotation projects from pilot to production scale. • Excellent written and verbal communication skills.
Data Scientist I, Risk Analytics
Company Description We’re Checkout.com. You might not know our name, but companies like eBay, Spotify, Klarna, Uber, and Sony do, because we’re behind many of the digital experiences you use every day. We are where the world checks out, enabling over 10 billion transactions yearly for more than one billion global shoppers. Whether you want to book a holiday, order food, renew a subscription, or check out online, there’s a good chance our tech powers the payments behind the scenes. Our platform helps the most ambitious businesses deliver effortless digital experiences, at scale. If you want to do career-defining work, you’ve come to the right place. We move fast, think globally, and believe great teams are built by hiring exceptional people with conviction, curiosity, and the desire to make an impact. With 20 offices across six continents and London as our HQ, we’re shaping the future of fintech – and we’re just getting started. We are looking for a highly technical, problem-solving Data Scientist I to join our Risk Analytics team in Ebene, Mauritius. You will be joining our dedicated Data Analytics and Tooling squad - the team responsible for building the robust data pipelines, interactive dashboards, and custom applications that empower our global Risk Operations to make fast, accurate decisions. At Checkout.com, high performance is a science, not an accident. In this role, you will be instrumental in optimizing how we manage risk through data. You will help build and scale our data infrastructure to run predictive anomaly detection models. We are actively scaling into new products, so you will have the ground-floor opportunity to integrate AI tools and shape our modern tech stack. You will be part of a dynamic team of builders who thrive on turning complex, high-volume data into scalable, automated solutions. What You Will Be Doing • Data Infrastructure & Pipeline Execution: Develop and maintain robust ETL pipelines, data models, and data controls using GCP, BigQuery, dbt, and Cloud Composer. You will ensure a clean, reliable single source of truth for the wider Risk organization. • Tooling & Process Optimization: Build intuitive custom UIs to directly support the Risk Operations team, making their day-to-day tasks and case management workflows faster and easier. • Actionable Dashboarding: Design, build, and maintain Looker dashboards that reduce manual ad-hoc requests and accelerate cross-functional decision-making. • AI Innovation & Modeling Infrastructure: Build the data infrastructure required to run anomaly detection and credit risk models. You will also help the team innovate by integrating new AI-based tools into our risk decisioning workflows. • Cross-Functional Partnership: Act as the trusted data partner for the Risk Operations team. You will rapidly execute ad-hoc data requests, troubleshoot data issues, and translate complex engineering data into clear business insights. #OneTeam About You • Data-Driven Problem Solver: You have 2+ years of applied working experience in Data Science, Data Engineering, or Data Analytics, with a proven track record of successfully delivering cross-functional projects. • Technical Architect: Advanced SQL fluency is non-negotiable. You have a good understanding of database management, ETL pipelines, and data orchestration. • The Modern Tech Stack: You will be working hands-on with tools like GCP, BigQuery, dbt, Looker, Cloud Composer, Databricks, GitHub, and ReTool. Any prior experience with these, or similar cloud-based data platforms, will be considered a strong advantage. • Detail-Obsessed Storyteller: You are an excellent communicator who can distill complex, "messy" data into clear narratives. You care deeply about data quality and strict validation before presenting findings to non-technical stakeholders. #NoRoomForApproximation • Bonus Points: Domain experience in Payments, Fraud, E-commerce, or Credit Risk. Additional Information Bring all of you to work We create the conditions for high performers to thrive, through real ownership, fewer blockers, and work that makes a difference from day one. Here, you’ll move fast, take on meaningful challenges, and be recognized for the impact you deliver. It’s a place where ambition gets met with opportunity, and where your growth is in your hands. We work as one team, and we back each other to succeed. So whatever your background or identity, if you’re ready to grow and make a difference, you’ll be right at home here. It’s important we set you up for success and make our process as accessible as possible. So let us know in your application, or tell your recruiter directly, if you need anything to make your experience or working environment more comfortable. Life at Checkout.com We understand that work is just one part of your life. Our hybrid working model offers flexibility, with three days per week in the office to support collaboration and connection. Curious about what it’s like to be part of our team? Visit our Careers Page to learn more about our culture, open roles, and what drives us. For a closer look at daily life at Checkout.com, follow us on LinkedIn and Instagram
Analyst I, Merchant Risk Analytics
Company Description We’re Checkout.com. You might not know our name, but companies like eBay, Spotify, Klarna, Uber, and Sony do, because we’re behind many of the digital experiences you use every day. We are where the world checks out, enabling over 10 billion transactions yearly for more than one billion global shoppers. Whether you want to book a holiday, order food, renew a subscription, or check out online, there’s a good chance our tech powers the payments behind the scenes. Our platform helps the most ambitious businesses deliver effortless digital experiences, at scale. If you want to do career-defining work, you’ve come to the right place. We move fast, think globally, and believe great teams are built by hiring exceptional people with conviction, curiosity, and the desire to make an impact. With 20 offices across six continents and London as our HQ, we’re shaping the future of fintech – and we’re just getting started. We are looking for a highly technical, problem-solving Data Scientist I to join our Risk Analytics team in Ebene, Mauritius. You will be joining our dedicated Data Analytics and Tooling squad - the team responsible for building the robust data pipelines, interactive dashboards, and custom applications that empower our global Risk Operations to make fast, accurate decisions. At Checkout.com, high performance is a science, not an accident. In this role, you will be instrumental in optimizing how we manage risk through data. You will help build and scale our data infrastructure to run predictive anomaly detection models. We are actively scaling into new products, so you will have the ground-floor opportunity to integrate AI tools and shape our modern tech stack. You will be part of a dynamic team of builders who thrive on turning complex, high-volume data into scalable, automated solutions. What You Will Be Doing • Data Infrastructure & Pipeline Execution: Develop and maintain robust ETL pipelines, data models, and data controls using GCP, BigQuery, dbt, and Cloud Composer. You will ensure a clean, reliable single source of truth for the wider Risk organization. • Tooling & Process Optimization: Build intuitive custom UIs to directly support the Risk Operations team, making their day-to-day tasks and case management workflows faster and easier. • Actionable Dashboarding: Design, build, and maintain Looker dashboards that reduce manual ad-hoc requests and accelerate cross-functional decision-making. • AI Innovation & Modeling Infrastructure: Build the data infrastructure required to run anomaly detection and credit risk models. You will also help the team innovate by integrating new AI-based tools into our risk decisioning workflows. • Cross-Functional Partnership: Act as the trusted data partner for the Risk Operations team. You will rapidly execute ad-hoc data requests, troubleshoot data issues, and translate complex engineering data into clear business insights. #OneTeam About You • Data-Driven Problem Solver: You have 2+ years of applied working experience in Data Science, Data Engineering, or Data Analytics, with a proven track record of successfully delivering cross-functional projects. • Technical Architect: Advanced SQL fluency is non-negotiable. You have a good understanding of database management, ETL pipelines, and data orchestration. • The Modern Tech Stack: You will be working hands-on with tools like GCP, BigQuery, dbt, Looker, Cloud Composer, Databricks, GitHub, and ReTool. Any prior experience with these, or similar cloud-based data platforms, will be considered a strong advantage. • Detail-Obsessed Storyteller: You are an excellent communicator who can distill complex, "messy" data into clear narratives. You care deeply about data quality and strict validation before presenting findings to non-technical stakeholders. #NoRoomForApproximation • Bonus Points: Domain experience in Payments, Fraud, E-commerce, or Credit Risk. Additional Information Bring all of you to work We create the conditions for high performers to thrive, through real ownership, fewer blockers, and work that makes a difference from day one. Here, you’ll move fast, take on meaningful challenges, and be recognized for the impact you deliver. It’s a place where ambition gets met with opportunity, and where your growth is in your hands. We work as one team, and we back each other to succeed. So whatever your background or identity, if you’re ready to grow and make a difference, you’ll be right at home here. It’s important we set you up for success and make our process as accessible as possible. So let us know in your application, or tell your recruiter directly, if you need anything to make your experience or working environment more comfortable. Life at Checkout.com We understand that work is just one part of your life. Our hybrid working model offers flexibility, with three days per week in the office to support collaboration and connection. Curious about what it’s like to be part of our team? Visit our Careers Page to learn more about our culture, open roles, and what drives us. For a closer look at daily life at Checkout.com, follow us on LinkedIn and Instagram
A place to build useful ways of working with artificial intelligence.
A teaching approach aimed at usage, not knowledge.
Data Engineer
WHO WE ARE: We think too much marketing isn’t us. It’s mass markets not audiences of one. Homogenous groups to be targeted, not individuals to be inspired. Segments to reach, not people with their own ideas and ambitions. It’s one size fits all and it’s dull. When it comes to individuals, we’re fierce. We stand up for individuality. We speak up against bland, broad-brush generalizations. We fight for solutions that adapt to the individual’s needs, beliefs, behaviors, and aspirations. And we commit to doing this in every aspect of our work for clients and their consumers. We actively foster an inclusive workplace where diversity and individual difference are valued and leveraged to achieve the agency’s vision. And most importantly we value every individual’s well-being. We are Fiercely Individual. HOW WE DO IT: At RAPP we are fiercely focused on the individual and how we can create value from every individual’s experience with a brand. We do this across three capability areas: customer centric consulting, creativity that inspires action and customer experience management. We're looking for someone with hands-on, business-oriented strategic and technical consulting to our clients for cloud infrastructure, automation solutions and solution architecture. In this role you will • Evaluate business needs, objectives and build algorithms and prototypes. • Responsible for designing, building, and supporting the components of data warehouse, such as ETL processes, databases, reports and reporting environments. • Conduct complex data analysis and report on results, analyze and organize raw data. • Identify opportunities for data acquisition by developing analytical tools and programs. • Collaborate with data scientists and architects on several projects. • Consolidate and optimize available data warehouse infrastructure. • Responsible for designing, building, and supporting the components of data warehouse, such as ETL processes, databases, reports and reporting environments. • Assembles performance statistics, analyzes them, and makes recommendations for improvements. • Establishes system documentation and ensures it is continually sustained. • Conceive analytics and business intelligence platform architecture for clients, including internal and third-party clients. • Collaborate with business and technology stakeholders in ensuring data warehouse architecture development and utilization. • Carry out monitoring, tuning, and database performance analysis. • Design, automate, build, and launch scalable, efficient and reliable data pipelines into production. • Perform root cause analysis and resolve production and data issues. What are we looking for? Besides a great attitude, You should have: • Experience and expertise with data models, data mining, and segmentation techniques • Experience with SQL database design • SQL Server Integration Service (SSIS) • Experience with programming languages (e.g. Java and Python) • Experience in combining raw data from different sources and conducting complex data analysis • Experience in building algorithms and prototypes and perform complex data analysis • Experience in design and implement ETL procedures for intake of data from both internal and external sources, as well as ensure data is verified and quality is checked • Experience in design and implement ETL processes and data architecture to ensure proper functioning of analytics, as well as client’s or third-party’s reporting environments and dashboard • Carry out monitoring, tuning, and database performance analysis • Minimum 1+ years of experience performing data warehouse architecture development and management • Minimum 4 years experience with technologies such as SQL Server, SQL Server Integration Service (SSIS), and stored procedures • Minimum 1+ years experience developing code, testing for quality assurance, administering RDBMS, and monitoring databases • High proficiency in dimensional modeling techniques and their applications • Minimum 1 + years experience in custom ETL design, implementation and maintenance • Advanced SQL skills is a must Requirements / Qualifications: • Desirable: Bachelor or master's degree in Computer Science or related technical field • Data engineering certification (preferable) • Ideally Intermediate English Proficiency (B2 reading, writing, and conversation).
Machine Learning Specialist
About The Role Operationalise machine learning models and AI capabilities into reliable, scalable, and secure production systems that power paid risk intelligence products. Key Responsibilities ML Systems & Deployment • Design and build scalable model training, deployment, and inference pipelines • Deploy models into production using CI/CD, containerisation, and cloud infrastructure • Ensure models meet performance, latency, and reliability requirements MLOps & Lifecycle Management • Implement model versioning, monitoring, and automated retraining mechanisms • Detect and respond to model drift, data drift, and performance degradation • Establish operational standards for AI systems Collaboration with Data Science & Product • Partner with Data Scientists to productionise and scale models • Work with Product and Engineering teams to integrate ML into customer‑facing products • Translate experimental work into robust production assets Governance, Security & Ethics • Ensure ML systems comply with privacy, security, and regulatory requirements • Support explainability, auditability, and responsible AI practices • Document models and operational decisions clearly Job Profile – Required Skills And Knowledge • 8+ years experience in ML engineering, MLOps, or software engineering roles • Strong software engineering skills in Python and cloud environments • Hands‑on experience with ML platforms (MLflow, Kubeflow, SageMaker) and Kubernetes Required Qualifications • Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field • MS in Big Data, AI or relevant fields
Data Scientist
About The Role Own the creation of decision‑grade intelligence products by applying advanced analytics and statistics to transform complex multi‑source data into trusted, monetizable customer offerings Key Responsibilities Analytics & Modelling • Design, build, validate, and maintain predictive and prescriptive models across travel, risk, and location domains • Apply statistical methods, machine learning, and experimentation to improve data accuracy, completeness, and trust • Develop domain‑specific metrics, benchmarks, and risk scoring frameworks Product & Commercial Responsibilities • Translate customer problems and market needs into analytical solutions and data products • Partner with Product Managers to define value propositions, pricing inputs, and success metrics • Contribute to roadmap prioritisation based on impact, feasibility, and monetisation potential Data Quality, Governance & Ethics • Define data quality rules, validation logic, and anomaly detection mechanisms • Ensure alignment with privacy, consent, and ethical AI standards in regulated environments • Support lineage, explainability, and auditability of analytical outputs Collaboration & Delivery • Work closely with Data Engineers to ensure model‑ready, reliable data pipelines • Collaborate with Machine Learning Engineers to operationalise models at scale • Communicate insights and recommendations clearly to technical and non‑technical stakeholders Job Profile – Required Skills And Knowledge • 7-8+ years' experience in applied data science roles • Strong proficiency in Python, SQL, and ML libraries • Ability to translate data into presentable stories. • Experience delivering customer‑facing, revenue‑generating data products Required Qualifications • Bachelor’s degree in computer science, Engineering, Information Systems, or related field • MS in AI, Big Data or relevant fields.
Data Engineer
About The Role Design, build, and operate the unified data platform and domain pipelines that underpin scalable, trusted, and monetisable data products. Key Responsibilities Data Platform & Pipeline Engineering • Design and implement batch and real‑time ingestion pipelines from internal and external sources • Build and maintain cloud‑native data lake and warehouse architectures • Ensure high availability, performance, and cost efficiency of data infrastructure Data Quality, Governance & Reliability • Implement automated data quality checks, observability, and SLA monitoring • Support master data management, metadata, lineage, and access controls • Embed security, privacy, and compliance controls into the platform by design Enabling Analytics, ML & APIs • Optimise datasets and pipelines for analytics, ML training, and API consumption • Work closely with Data Scientists and ML Engineers to support feature and model needs • Enable self‑service data access patterns for downstream teams Continuous Improvement & Scale • Continuously improve performance, scalability, and reliability of pipelines • Introduce modern tooling and standards to reduce operational overhead • Contribute to long‑term platform roadmap and AI readiness Job Profile • 5+ years experience in data engineering or platform roles • Strong experience with SQL, Python, Spark, and cloud platforms (AWS, Azure, or GCP) • Experience operating data platforms in production at scale Required Qualifications • Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field • MS in Big Data, AI or relevant fields • Certifications such as PMI‑ACP, PMP, SAFe, CSM, or equivalent are beneficial
Document Analyst (Maurice)
Job Title: Document Analyst Location: Remote (Worldwide) Job Summary: The Document Analyst is responsible for reviewing, verifying, and analyzing documents to ensure accuracy, authenticity, completeness, and compliance with organizational policies and regulatory standards. This role supports operational integrity by identifying discrepancies, validating information, and assessing documentation for potential risk, fraud, or procedural gaps. Responsibilities • Analyze and validate data extracted from a wide variety of documents, including government-issued IDs, proof of address, financial statements, legal contracts, and medical forms. Ensure extracted fields (name, date, document number, etc.) are accurate and complete. • Identify sophisticated document fraud, including photoshopped IDs, counterfeit documents, and deepfake verification attempts. Use forensic analysis techniques to spot anomalies in security features (holograms, watermarks, microprint). • Handle complex edge cases where documents are damaged, non-standard, or from unfamiliar jurisdictions. Use research skills and domain knowledge to make accurate determinations on document validity and data interpretation. • Collaborate with Policy and Product teams to create, test, and refine annotation guidelines account for global document diversity and emerging fraud vectors. • Provide structured feedback to machine learning engineers and data scientists on model performance. Identify systematic errors in OCR or data extraction and contribute to “golden datasets” used for model training and evaluation. • Perform quality checks on document annotations and verifications completed by junior analysts or automated systems. Maintain high inter-annotator agreement (IAA) and ensure compliance with regulatory requirements. • Ensure document processing workflows comply with global regulations, including KYC (Know Your Customer), AML (Anti-Money Laundering), GDPR, and eIDAS (Electronic Identification and Trust Services). • Identify opportunities to streamline document review workflows, improve tooling, and reduce manual touchpoints without compromising accuracy or security. Requirements • Minimum of 3 years of experience in Document Analysis, Identity verification, KYC/AML Operations, or Data Extraction within fintech, legal tech, trust & safety, or AI training sectors. • Deep knowledge of global identity documents (passports, driver’s licenses, national IDs), financial documents (bank statements, pay stubs), and/or legal documents (contracts, incorporation papers). • Proven ability to identify sophisticated document fraud, including manipulation techniques, forgery indicators, and biometric discrepancies. • Experience with document verification tools, OCR software, or annotation platforms. Familiarity with data formats such as JSON, XML, or CSV for structured data output. • Strong understanding of KYC/AML frameworks, data privacy regulations (GDPR, CCPA) and industry standards for identity verification.
Data Set Curator (Maurice)
Dataset Curator Job Summary: We are seeking for a Dataset Curator who is responsible for designing, maintaining, and optimizing high-quality datasets for AI, Machine Learning (ML), and Large Language Model (LLM) projects. The Dataset Curator works closely with data scientists, AI trainers, and engineers to gather, clean, validate, and annotate datasets across multiple domains, ensuring the data supports robust AI model training and evaluation. The dataset curator must understand dataset diversity, bias detection, quality assessment, and metadata management. This role is critical to improving AI performance, dataset reliability, and data-driven decision-making. Key Responsibilities • Curate, collect, and structure datasets for AI and ML training purposes. • Validate dataset accuracy, completeness, and consistency. • Annotate and label datasets according to project-specific guidelines. • Identify and correct data inconsistencies, duplicates, and anomalies. • Maintain metadata and documentation for datasets. • Collaborate with AI trainers and data engineers to define dataset requirements. • Ensure datasets are ethically sourced and free from biases. • Continuously monitor dataset quality and propose improvements. Job Requirements Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Information Systems or related field. Proficiency in Excel, Google Sheets, SQL, and/or Python for dataset handling. Knowledge of data cleaning, normalization, and transformation techniques. Familiarity with data annotation tools and platforms. Understanding of structured, semi-structured, and unstructured datasets. Experience with database management and version control systems. Awareness of AI dataset ethics and bias mitigation. Required Certifications such as Google Data Analytics Certificate (advantage), Data Management or Curation Certification, AI/Data Annotation Training (optional but preferred) 3-5 years proven experience in dataset curation, data analysis, or data management roles. Experience handling large-scale datasets for AI, ML, or analytics projects.