Senior Probabilistic Record Linkage Specialist

SLK INDUSTRIAL SUPPORT AND LIGHTING; Abu Dhabi; A distancia; AED 250.000 - 420.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

100% remote work

Competitive compensation based on exp.

Professional development

Descripción de la vacante

SLK INDUSTRIAL SUPPORT AND LIGHTING is seeking a Senior Probabilistic Record Linkage Specialist to design, develop, and validate cross-dataset matching solutions. This fully remote role emphasizes probabilistic matching, data quality, privacy, and scalable pipelines, with a focus on large datasets and complex entity resolution.

You will collaborate with data engineering, analytics, and compliance teams, implement blocking and candidate generation, and establish thresholds and validation metrics.

Formación

• Strong background in statistics, data science, or related quantitative field.
• Hands-on experience with probabilistic record linkage and entity resolution.
• Proficiency in Python or R and SQL for large, multi-source datasets.
• Familiarity with privacy, data governance, and responsible data handling.

Responsabilidades

• Design probabilistic record linkage frameworks for large datasets.
• Develop matching models and compute match probabilities.
• Set thresholds, rules, and confidence levels for linkage results.
• Handle missing values and data quality issues in linkage workflows.
• Implement blocking, indexing, and candidate-generation techniques.
• Develop automated quality checks and reproducible validation workflows.
• Collaborate with data engineering, analytics, and compliance teams.
• Document methodologies, assumptions, and limitations; present results.

Conocimientos

Analytical thinking

Problem solving

Attention to detail

Communication skills

Remote work management

Educación

Quantitative degree

Herramientas

Python

R

SQL

Cloud platforms

Descripción del empleo

Senior Probabilistic Record Linkage Specialist

Location: United Arab Emirates (Remote)

Employment Type: Full-Time

Work Arrangement: 100% Remote — Work From Home

Level: Senior

About the Role

We are seeking an experienced Senior Probabilistic Record Linkage Specialist to design, develop, and validate methodologies for identifying and matching records that refer to the same individuals, organizations, entities, or events across multiple datasets. The successful candidate will apply probabilistic matching, statistical inference, data quality techniques, and machine learning to resolve inconsistent, incomplete, and duplicated records. This fully remote role requires advanced analytical expertise, strong programming capabilities, and a thorough understanding of data governance and privacy considerations.

Key Responsibilities

• Design and implement probabilistic record linkage frameworks for large and complex datasets.
• Develop matching models to identify equivalent records across databases and information systems.
• Apply statistical techniques to calculate match probabilities using identifying attributes and comparison patterns.
• Establish appropriate matching thresholds, decision rules, and confidence levels.
• Develop methods for handling missing values, inconsistent formats, typographical errors, and incomplete identifiers.
• Apply blocking, indexing, and candidate-generation techniques to improve matching efficiency.
• Implement deterministic and probabilistic matching approaches where appropriate.
• Evaluate similarity measures for names, addresses, dates, identification attributes, and organizational information.
• Develop entity resolution procedures to identify duplicate records and consolidate fragmented data.
• Validate linkage accuracy using precision, recall, false-match rates, and missed-match rates.
• Conduct clerical review analysis and establish procedures for resolving ambiguous matches.
• Investigate data-quality issues, systematic matching errors, and sources of linkage bias.
• Apply privacy-preserving techniques and appropriate controls when processing sensitive or personally identifiable information.
• Collaborate with data engineering, analytics, compliance, and business teams to integrate record linkage solutions.
• Optimize matching algorithms, processing pipelines, and computational performance.
• Develop automated quality checks, monitoring procedures, and reproducible validation workflows.
• Prepare technical documentation covering methodologies, assumptions, matching thresholds, and limitations.
• Present linkage performance results and recommendations to technical and non-technical stakeholders.

Qualifications and Experience

• Bachelor's or master's degree in Statistics, Mathematics, Data Science, Computer Science, Information Systems, or a related quantitative discipline.
• Significant professional experience in record linkage, entity resolution, data matching, or advanced data quality analytics.
• Strong understanding of probabilistic matching theory, statistical inference, and classification techniques.
• Practical experience with probabilistic record linkage frameworks and entity resolution methodologies.
• Proficiency in Python or R and relevant data processing and statistical libraries.
• Advanced SQL skills and experience working with large, multi-source datasets.
• Knowledge of string similarity measures, fuzzy matching, blocking, and candidate-generation techniques.
• Experience evaluating matching accuracy, confidence scores, and threshold selection.
• Understanding of data standardization, deduplication, and master data management principles.
• Familiarity with privacy, information security, and responsible handling of sensitive data.
• Experience with distributed data processing or cloud-based analytical platforms is advantageous.
• Ability to investigate complex matching errors and recommend methodological improvements.
• Strong analytical reasoning, problem-solving, and attention to detail.
• Excellent written and verbal communication skills.
• Ability to manage complex projects independently in a fully remote working environment.

What We Offer

• 100% remote working arrangement within the stated employment framework.
• Competitive compensation based on qualifications and professional experience.
• Opportunities to work on advanced data integration and entity resolution projects.
• Professional development and continuous learning opportunities.
• Collaborative environment with international and multidisciplinary teams.