Data Scientist / ML Engineer & SearchThis is a hands-on Lead / Architect role focused on search personalization and recommendation systems. You will review and enhance an existing intelligent search platform, design and implement recommendation algorithms, and continuously improve search quality and relevance across a large-scale enterprise environment.Working on top of an enterprise search solution for a large-scale environment, you will apply advanced machine learning and data science techniques to drive personalized user experiences. ResponsibilitiesReview the existing search personalization strategy and identify areas for improvementDesign, develop, and optimize recommendation algorithms, including feature engineering and signal selectionLeverage behavioral signals such as searches, clicks, views, and interactions to drive personalized recommendationsDesign, evaluate, and tune machine learning models using relevant offline and online performance metricsDefine and optimize relevance, ranking, and scoring methodologiesEvaluate and continuously improve recommendation quality across the full user journeyCore RequirementsStrong background in Data Science and Machine LearningHands-on experience building search platforms and recommendation systemsExperience with personalization, user affinity modeling, and behavior analysisSolid understanding of ranking algorithms, relevance scoring, and recommendation techniquesExperience engineering behavioral signals from user interactionsStrong Python skills and experience with ML and data processing librariesKnowledge of information retrieval concepts, relevance, and ranking methodologiesExperience working with large-scale datasets and production ML systemsNice to HaveExperience with Coveo, Elasticsearch, or OpenSearchKnowledge of vector search, semantic search, and embeddingsExperience designing hybrid search architecturesExperience integrating machine learning capabilities into enterprise applicationsFamiliarity with SAP ecosystems or enterprise content platformsThe Profile We're Looking ForArchitect-level thinking: You can assess an end-to-end search and personalization ecosystem, identify weaknesses, and define a scalable improvement strategyStrong signal intuition: You understand which user behaviors matter and how to transform raw events into meaningful recommendation featuresProduction-focused mindset: You have successfully delivered ML solutions operating at scale in real-world environmentsPlatform-agnostic approach: You focus on solving business and user problems rather than relying on a specific search technology Show more Show less