Are you interested in working with the World’s leading AI-First Quality Engineering Company? We are looking for a Data Scientist/ RAG Specialist to join our growing team in Canada!

Role: Data Scientist/ RAG Specialist Location: CAN/MEX/ARG(remote) Strong knowledge of search engineering concepts, including indexing, retrieval, scoring, ranking, relevance, and production search system tradeoffs.

The Search Data

Scientist will design, evaluate, and improve search and discovery solutions that help users find relevant Client journalism quickly and reliably across large, diverse content collections. As a member of cross-functional project teams, the Search Data Scientist will combine data science, information retrieval, and search engineering expertise to tune production search systems and deliver measurable improvements in relevance, quality, and performance. The team works closely with product, engineering, editorial, and other functions across the organization to define search quality, build robust evaluation practices, and develop scalable retrieval and ranking solutions.

This is for Text, Video and Image search with Meta Data. Design search experiments and evaluation frameworks, including offline relevance judgments, benchmark datasets, online testing, and analysis of quality and performance at scale. Establish repeatable approaches for relevance tuning across large and evolving content collections, accounting for freshness, metadata quality, content type, and query intent.

Support the full search development lifecycle, from problem definition and prototyping through integration, deployment, monitoring, and iteration. Communicate analysis and present findings clearly,



adapting to a range of technical and business audiences. 3+ years of relevant data science, search, or information retrieval experience, with strong proficiency in Python, and experience working with large-scale semi-structured data. ~ Bachelor’s degree in Data Science, Computer Science, Information Retrieval, or a related field. ~ Strong knowledge of search engineering concepts, including indexing, retrieval, scoring, ranking, relevance, and production search system tradeoffs. ~ Experience with embedding-based retrieval, approximate nearest-neighbor search, vector index configuration, and lexical-vector score combination or fusion strategies. ~ Experience developing and testing query classification approaches, including query classification, intent detection, query expansion, and routing. ~ Experience with post-retrieval techniques such as learning-to-rank or model-based reranking, filtering, deduplication, thresholding, and result diversification. ~ Demonstrated ability to validate search algorithms at scale using offline and online evaluation methods, including relevance judgments, benchmark sets, A/B testing, and statistical analysis. ~ Familiar with ML engineering and ML Ops practices, with a track record of delivering runtime solutions ~ An effective communicator who can tailor analysis and presentations to both technical and non-technical audiences ~ Advanced-level skilled competency in written and spoken English Experience in news media or working with news as data strongly preferred Master's degree in Data Science or a related field Eagerness to learn the technical nuances of large-scale media operations and identify opportunities within evolving systems #

📌 Data Scientist/ RAG Specialist (Toronto)
🏢 QualityAI
📍 Toronto