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Emil O. from United States

Emil O.

United States 1-2 years
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Languages
English
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About

Emil O. is a seasoned Data Analyst with over three years of experience specializing in large-scale data quality analysis, multilingual dataset evaluation, and business intelligence reporting. He has a proven track record of processing and analyzing over 150,000 data records in sectors including telecommunications, legal, media, and technology. Emil excels in quality metrics analysis, statistical process control, and data-driven decision support, leveraging his native English fluency and proficiency in German, Spanish, French, and Dutch to analyze international datasets effectively. As a Senior Data Quality Analyst at GlobalLingua AI Services, Emil oversees the quality assurance of over 1,400 multilingual data records weekly, achieving a 94.8% error detection accuracy using dynamic quality frameworks. His career highlights include implementing processes that reduced data errors by 42% and increased client satisfaction by 36%. Emil’s educational background includes a Master's in Data Science with a focus on Machine Learning and NLP from the University of Texas, complemented by certifications in NLP applications and advanced data quality assessment.

Experience

  • Senior Data Quality Analyst

    GlobalLingua AI Services · 2022 — Present
    Weekly analysis and validation of over 1,400 multilingual data records within the telecommunications, legal, and media sectors utilizing systematic evaluation frameworks. Achieved a 94.8% error detection accuracy by employing DQF (Dynamic Quality Framework) and MQM (Multidimensional Quality Metrics) statistical methods. Conducted comparative assessments of AI-generated outputs focusing on relevance, accuracy, and business value. Created and updated quality assessment frameworks tailored for legal terminology, technical documentation, and marketing analytics. Oversaw data consistency databases to maintain standardization and efficiency in analysis projects and client deliverables. Collaborated with analysts across six countries to establish data quality standards and address analytical challenges. Produced detailed analytical reports that highlighted error patterns, data trends, and suggestions for model optimization. Led quarterly calibration sessions reaching over 91% inter-rater agreement among a team of 13 analysts.

  • Data Annotation Specialist & Quality Analyst

    ContentAI Labs UK · 2021 — 2022
    Processed and annotated over 62,000 multilingual data samples for machine learning applications, including NER, sentiment analysis, and classification systems. Achieved an 87.5% data consistency rate by adhering to guidelines and performing continuous quality monitoring throughout high-volume projects. Classified data across various dimensions such as topic, sentiment, intent, formality level, and target audience using structured taxonomies. Identified errors in AI model outputs through evaluation of syntax, semantics, and cultural adaptation with statistical error analysis. Carried out systematic fact-checking to verify claims against authoritative multilingual sources in telecommunications and digital media. Executed A/B testing to enhance data quality and task completion rates in diverse content domains. Worked alongside data scientists to provide insights on model performance and data optimization strategies.

  • Data Quality Specialist & Validation Analyst

    UK Data Intelligence Ltd · 2020 — 2021
    Reviewed and validated over 47,000 data records for projects focused on conversational AI, text classification, and information extraction analytics. Achieved an 84.6% quality approval rate on first-pass reviews by focusing on data accuracy and completeness. Evaluated multilingual datasets for accuracy, semantic consistency, and structural relevance based on business applications. Ensured data validation through format compliance, completeness, and adherence to quality standards. Utilized structured evaluation rubrics to assess data quality and pinpoint areas for improvement. Developed quality reports that documented error frequencies, pattern analysis, and performance trends for stakeholders. Supported training initiatives by mentoring new team members in data validation tools and best practices.

Skills & Expertise

BiotechnologyAI and Data ScienceData Visualization SpecialistData AnalystSoftware and Mobile Development

Education

  • Master of Science in Data Science
    University of Texas · 2021 — 2023
  • Bachelor of Science in Data Analysis
    University of Texas · 2018 — 2021