Sr. Data Scientist- Computer Vision, Data & Machine Learning (dml)

Amazon Amazon · Big Tech · Arlington, VA · Data Science

Develop computer vision models on overhead imagery for a government customer, owning the entire ML development lifecycle from data exploration and feature engineering to model training, evaluation, and delivery. This role operates on classified networks and requires a Top Secret security clearance.

What you'd actually do

  1. Run data conversion pipelines to transform customer data into the structure needed by models for training
  2. Perform EDA on the customer data
  3. Train deep neural network models on overhead imagery
  4. Develop and implement hyper-parameter optimization strategies
  5. Test and Evaluate models and analyze results

Skills

Required

  • 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
  • Knowledge of AWS tech stack (e.g., AWS Redshift, S3, EC2, Glue)
  • Bachelor's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science
  • 2+ years of experience with machine learning, statistical modeling, data analysis tools and techniques, and performance parameters for computer vision delivery requirements
  • Current, active US Government Security Clearance of Top Secret or above

Nice to have

  • 3+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience
  • Experience managing data pipelines
  • Experience as a leader and mentor on a data science team
  • Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science
  • Familiarity with internals of LLMs, VLMs, and traditional Computer Vision object detection models

What the JD emphasized

  • US Citizen and currently possess and maintain an active Top Secret security clearance
  • develop computer vision models on overhead imagery
  • entire machine learning development life cycle
  • Train deep neural network models on overhead imagery

Other signals

  • develop computer vision models on overhead imagery
  • entire machine learning development life cycle
  • train deep neural network models