Data Scientist

Position Title: Data Scientist (Remote) Location: Lexington, MA, USA, 02421 Duration: 05 months Contract on W2 (possible extension) • • • • • • • • • • • • • • • • • • • • • NO C2C • • • • • • • • • • • • • • • • • • Note • Candidates must should have an Active Clearance (secret/top secret, etc.) Only US Citizen Position Description: • Designs, develops, and implements methods, processes, and systems to consolidate and analyze diverse data sets including structured and unstructured. • Develops software programs, algorithms, dashboards, information tools, and queries to clean, model, integrate and evaluate datasets. Keeps abreast of new analytic methodologies and technologies. • Collaborates with functional business units to drive business solutions and direction. Key Responsibilities include but not limited to: • Design, implement, and maintain enterprise-scale search solutions using Apache Solr • Develop and optimize semantic search capabilities using vector embeddings and neural search models • Build custom indexers and indexing pipelines that support vector embeddings alongside traditional text fields • Implement and tune Approximate Nearest Neighbor (ANN) algorithms for efficient similarity search at scale • Design and optimize similarity functions (cosine, dot product, Euclidean) for various search use cases • Build hybrid search systems that combine traditional keyword-based search with vector-based semantic search • Perform traditional relevancy engineering including query analysis, field weighting, boosting strategies, and result tuning • Conduct relevancy analysis using quantitative metrics and qualitative evaluation methods • Monitor search performance metrics and implement continuous improvements • Work cross-functionally with product, engineering, and data teams to define search requirements Required Qualifications: • 5+ years of hands-on experience with Apache Solr or Lucene in production environments • Strong expertise in traditional relevancy engineering including query parsing, field boosting, function queries, and relevance tuning • Proven experience conducting relevancy analysis using both automated metrics and manual evaluation techniques • Strong expertise in vector embeddings and their application to semantic search • Proven experience building hybrid search systems that combine keyword and vector-based approaches • Knowledge of search relevance metrics (NDCG, MRR, precision/recall) • Excellent problem-solving and analytical skills • Strong communication skills and ability to work in collaborative environments Nice to Have: • Databases and Data Engineering for Big Data • Elasticsearch • Statistical Methods Clearance: Candidates should have an active clearance (secret/top secret, etc.) in order to be considered for this position due to the nature of the work being done. Interview Process: • 1st round interview will be a Zoom with the hiring manager. 2nd round interview will be a Zoom with additional team members as needed.