
Sr. Data Scientist
Skills
About the role
Sr. Data Scientist (AWS, AI, ML)
Location: Mostly Remote – Onsite 1x/month in Reston, VA (must reside in DC, MD, or VA)
Company Overview
Glint Tech Solutions is a women-owned global staffing and IT recruiting firm connecting top technical talent with leading enterprise clients across the United States and Canada.
Project Description
Our client, a federal healthcare insurance organization, has an immediate need for a Senior Data Scientist to identify and solve business problems using statistical modeling, machine learning, AI, operations research, and data mining. The selected candidate will own high-impact data science projects from inception through completion, contribute technically throughout, refine product requirements with Product teams, coordinate the efforts of other data scientists, and interface with stakeholders across the organization. This is a mostly remote role with onsite requirements 1–2 times per month in the DC Metro area. Candidates must reside in the DC, MD, or VA area or a touching state; travel expenses will not be covered.
Key Responsibilities
Identify and solve complex business problems using statistical modeling, machine learning, AI, operations research, and data mining techniques
Own high-impact data science projects end-to-end, from inception through production deployment
Lead and coordinate the efforts of other data scientists contributing to shared projects
Build, train, and deploy ML solutions using AWS services including SageMaker, Bedrock, Kendra, and Lambda
Write production-ready code including proper documentation and unit tests
Apply advanced machine learning methods including k-nearest neighbors, random forests, and ensemble methods
Communicate across product teams and with customers to educate on AI, ML, and statistical models
Refine product requirements in collaboration with Product teams and interface with stakeholders across departments
Mandatory Skills
8+ years of experience as a Data Scientist with both model building and deployment experience
Advanced Python and SQL proficiency
Advanced proficiency in Python and Spark/Scala for statistical analysis, data modeling, ML, and ETL processes
Intermediate to advanced data visualization skills using Python
Solid hands-on knowledge of AWS SageMaker, Bedrock, Kendra, and Lambda (required)
Ability to write production-ready code including documentation and unit tests
Experience with ML methods including k-nearest neighbors, random forests, and ensemble methods
Strong AI/ML expertise across Machine Learning, Deep Learning, Decision Trees, Random Forest, Neural Networks, Supervised/Unsupervised Learning, Forecasting, Predictive Modeling, and Clustering
Deep knowledge of machine learning fundamentals, data mining, and statistical predictive modeling
Proficiency with Python ML and data pre-processing libraries - Scikit-Learn, NumPy, Pandas
Strong software prototyping and engineering skills across Python, R, and Spark/Scala
Ability to initiate and drive projects to completion with minimal guidance
Strong communication skills for presenting analysis results clearly and effectively
Degree preferred; 4 additional years of experience may substitute for a degree
Nice-to-Have Skills
Experience with Agentic AI
Familiarity with statistical packages such as R, MATLAB, SPSS, SAS, or Stata
Proficiency with healthcare analytics and data structures
Experience with big data technologies, ETL, statistics, causal inference, and simulation
Experience with large data sets and distributed computing (Hive/Hadoop)
Prior experience leading data science projects or teams independently
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