Senior Data Scientist - Hybrid, Impactful ML Leader

MarginEdge

Arlington (VA)

Hybrid

USD 165,000 - 185,000

Full time

4 days ago
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Benefits offered by this job

Unlimited Paid Time Off
Health, Dental, Vision Insurance
401(k) with matching
Stock options
Parental leave

Job summary

MarginEdge in Arlington, VA is seeking a Senior Data Scientist to research, develop, and deploy innovative machine learning and statistical models. You will embed with product, engineering, and sales/marketing teams, owning work end-to-end from idea through deployment in AWS.

Responsibilities include designing data pipelines, evaluating models, and collaborating with engineers to deliver production-ready solutions. Hybrid work in the DC metro area is preferred.

Qualifications

  • Experience shipping end-to-end ML models in production.
  • Ability to design scalable data science pipelines.
  • Experience communicating statistical methods to diverse audiences.

Responsibilities

  • Collaborate with product and stakeholders to identify data science opportunities.
  • Research, develop, and deploy ML models to solve business problems.
  • Design scalable pipelines to transform raw data into insights.
  • Evaluate and optimize models for accuracy and performance.
  • Collaborate with engineering to implement solutions in AWS.
  • Stay updated on ML and AI advances; report KPIs to stakeholders.
  • Provide mentorship and code reviews to teammates.

Skills

Python
SQL
Machine Learning
LLMs
AWS
Data pipelines
Git
Claude Code
Communication
Problem-solving

Tools

Claude Code

Job description

MarginEdge in Arlington, VA is seeking a Senior Data Scientist to research, develop, and deploy innovative machine learning and statistical models. You will embed with product, engineering, and sales/marketing teams, owning work end-to-end from idea through deployment in AWS.

Responsibilities include designing data pipelines, evaluating models, and collaborating with engineers to deliver production-ready solutions. Hybrid work in the DC metro area is preferred.

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