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Open nowFirst seen 3 days ago

Sr. Data Scientist (AWS, AI, ML)

Glint Tech Solutions LLC139 open roles

Where
Reston, Virginia, United States
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Your applicationOpen nowSr. Data Scientist (AWS, AI, ML)Glint Tech Solutions LLC · Reston, Virginia, United States

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on Glint Tech Solutions LLC's own form.

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The clock on this job

Early applications get read.

12.1% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.1%7 days
  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: first seen 3 days ago

The posting

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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