Data Analyst (Arabic)

🇪🇸Remote - Spain3w ago

Corporate Data & Analytics Data Analysis Natural Language Processing Multilingual Data Text Analysis

Role Snapshot

As a Data Analyst (Arabic), you will support Lightcast's global data initiatives by analyzing and improving multilingual data quality, working with Linguistics and Engineering teams to develop parsers and ensure high-quality data delivery across global markets.

Key Responsibilities: Analyze and improve data quality of multilingual text classifiers, develop parsers across multiple geographies and Arabic dialects, translate taxonomies (Skills, Titles, Occupations), and clean data using Excel and other analysis tools.

Skills & Tools: Proficiency in Arabic (reading, writing, and syntax analysis), advanced Excel skills (VLOOKUPs, data cleanup, functions), SQL and RegEx knowledge, text analysis or machine learning principles, and strong attention to detail with ability to work independently.

Qualifications: Bachelor's degree in Linguistics, Data Analytics, Natural Language Processing, or related field preferred; knowledge of multiple Arabic dialects and additional languages preferred; experience with data analysis tools and understanding of complex instructions.

Location: Remote - Spain

Compensation: Not provided by employer. Typical compensation for this role is €28,000 – €38,000/year based on title, seniority, location, and 8-month contract duration.

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Job Description

As a Data Analyst (Arabic), you will support Lightcast's global data initiatives by analyzing and improving multilingual data quality. Working closely with Linguistics and Engineering teams, you will help develop parsers, evaluate text classifiers, and translate key taxonomies to ensure we deliver high-quality data to customers across global markets. This is a full-time (40 hours per week) independent contractor position for up to 8 months and requires candidates to provide their own laptop and reliable internet access. Major Responsibilities::

Analyze and improve the data quality of multilingual text classifiers

Partner with Linguistics and Engineering teams to develop parsers across multiple geographies and Arabic dialects

Translate taxonomies including Skills, Titles, and Occupations

Analyze and clean data using Excel and other data analysis tools

Apply language, data, and text analysis expertise to support high-quality global data

Education & Experience::

Proficiency in reading and writing Arabic required, including an understanding of Arabic syntax and structural analysis

Reliable laptop and internet access required

Knowledge of multiple Arabic dialects preferred

Knowledge of additional languages preferred

Bachelor's degree in Linguistics, Data Analytics, Natural Language Processing (NLP), or a related field preferred

Experience with Microsoft Excel, including VLOOKUPs, data cleanup, and functions

Knowledge of query languages such as SQL

Advanced knowledge of rule writing using regular expressions (RegEx)

Knowledge of text analysis or machine learning principles

Experience with data analysis using tools such as Excel

Ability to perform repetitive, detail-oriented work with accuracy and consistency

Ability to follow complex instructions, navigate ambiguity, and work independently

Strong sense of urgency, organization, and time management

Lightcast is a global leader in labor market insights with our headquarters located in Moscow, ID (US) and other offices in the United Kingdom, Europe, and India. We work with partners across six continents to help drive economic prosperity and mobility by providing the insights needed to build and develop our people, our institutions and companies, and our communities.

Lightcast is proud to be an equal opportunity workplace and does not discriminate on the basis of federally protected statuses. Lightcast has always been, and always will be, committed to diversity of thought and unique perspectives. We seek dynamic professionals from all backgrounds to join our teams, and we encourage our employees to bring their authentic, original, and best selves to work.