Beruk Merid

• Builds, develops and maintains Intuit's taxonomy, focusing on controlled vocabularies, data labels, classification, and ontology, as well as consistent practices.
• Conducts tests and tracks software and website progress.
• Uses Data Analysis to create concept-based tags, identifies trends and delivers insights.
• Evaluates the quality of machine learning classification.
• Enriches knowledge models through data evaluation and entity extraction.
• Skillfully groups concepts based on their similarity in scope, definition, and relationship to other concepts.
• Possesses proficiency in several softwares and tools, including Poolparty - a Taxonomy Software Tool - as well as Postman - an Entity Extractor.
• Collaborates extensively with multiple product managers and stakeholders across the organization in order to effectively address various business requirements and demands.
• Utilizes and improves generative AI to help automate identifying relationships within digital content.
• As the sole taxonomist in my department, I have taken ownership of our taxonomy and added over 1,200 concepts and about 4,000 labels to go with those concepts within 6 months. While adding those concepts and labels, I also conduct data analyses to examine attributes, labels, and data.

• Managed development & maintenance of eBay’s growing taxonomy
  across different locales to ensure optimal user experience.
• As part of the Product Knowledge Data Intelligence team, I completed quarterly competitor analyses and A/B testing to enhance the catalog's performance for eBay sellers and buyers. This led to around a 5% quality boost each quarter.
• Conducted thorough analyses to create and modify the most relevant
  categories, attributes, and values for products in eBay's catalog. I used a range of research methodologies to gather and analyze data from various sources.
• Responded to information needs efficiently by implementing & modifying category aspect vocabulary tools and processes.
• Consistently met and exceeded my end of quarter initiative goals by at least 110% throughout the entire year.

• Implemented organization of sensitive data through ontology and taxonomy.
• Analyzed large sets of data related to regional markets, identified patterns, and labeled the information.
• Generated categorized datasets of various ads, search terms, and user feedback to analyze user intent and improve UX.
• Reviewed and spotchecked content for tagging and labeling for relevance, search purposes, taxonomy and product classification.
• Consistently improved content relevance in algorithms and ads every quarter.
• As a Senior Analyst, I managed and helped onboard new hires.

• Streamlined Walmart's hierarchy by categorizing appropriate levels of ranking.
• Collaborated with engineers and catalog team to enhance online customer shopping experience based on user intent.
• Devised guidelines for numerous evaluation tasks in Confluence.
• Generated Excel sheets of 10k queries for analysts to tag and evaluate in Online Grocery, as well as spot-checked the completed files.
• Despite having a KPI goal of deciphering and labeling 450 long strings of data weekly, I was able to exceed expectations by completing an average of 600 strings per week, while managing my other tasks efficiently.
• Directed international team projects by providing project score, quality summary, and statistics for VP's weekly review.
• Categorized tagged queries by mapping to the most granular product type.
• I spearheaded a deep research project which involved analyzing, labeling and classifying a set of 50K queries, resulting in an impressive improvement of our Machine Learning process score from 68% to 89% within one year.

Similar responsibilities that are listed above.

(Worked at Yahoo twice. For 2.5 years in 2016 and returned to Yahoo in 2021 after my team was laid off at Walmart Labs.)

• Collaborated on a confidential project aimed at improving software performance both before and after its release, leading to enhanced user experience across global markets.
• Conducted extensive market research to establish accuracy standards within the software, maintaining rigorous attention to detail throughout data review and testing to ensure top-quality products.
• Organized and facilitated engaging group training sessions and performance reviews, which significantly contributed to the creation, development, and implementation of new and optimized features within the software.
• Developed a creative approach to data accuracy by thoroughly assessing application features and functionality, thereby creating software that consistently performs at a high level across all user platforms.