Data Scientist

•  Designs, develops, and implements methods, processes, and systems to consolidate and
• analyze diverse data sets including structured and unstructured.
•  Develop software programs, algorithms, dashboards, information tools, and queries to
• clean, model, integrate and evaluate datasets. Keeps abreast of new analytic
• methodologies and technologies.
•  Collaborate 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. Do not submit
• candidates if they do not meet this requirement.

Work Location

•  This position has the ability to work hybrid, remote or onsite. Please list which the
• candidate prefers in the write up.

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.

Must Have

Data/Reporting

• Data Analysis 5 years
• R, Python, SQL, and Machine Language Algorithms and Data Analysis. 5 years

Degree Level

Bachelor's Degree Yes

Experience

• Currently holds a Secret Clearance (OR a higher clearance) Yes
• Quantitative relevancy analysis and tuning 5 years
• Vector embeddings semantic search 5 years

Programming

C/C++, Java, Python, Bash, SQL, Java Script / HTML / CSS, Matlab 5 years

Software Tools

Apache Solr and creating data pipelines for search products 5 years

Nice to Have

Data/Reporting

• Databases and Data Engineering for Big Data 0 years
• Elasticsearch 0 years
• Statistical Methods 0 years

Duration: 6 Months

Security Clearance Requirement: Yes

Security Clearance Level: Active Secret

Location: Lexington, MA 02421

Pay Range: $75-$100 an hour

Requirements

Benefits