Data Scientist, Python and AWS

Summary

Peregrine Advisors is an AI and data innovation hub helping government solve complex problems and deliver better outcomes. The Data Scientist will transform structured, semi-structured, and unstructured client data into defensible analytical processes and outcomes using Python, SQL, AWS, statistics, and machine learning. The role also involves evaluating and documenting models, building repeatable analytical pipelines, and communicating findings to decision-makers.

Responsibilities

• Frame analytical questions with the people who own the mission, and turn them into designs that can actually be tested
• Build analyses and models in Python and Structured Query Language (SQL) on cloud-native data platforms hosted in Amazon Web Services (AWS)
• Build models that earn their place: forecasting, classification, risk scoring, and anomaly detection matched to the question, the data, and the scrutiny a federal decision has to survive
• Design the evaluation that shows a model is fit for a client environment, with baselines, validation designs, error analysis, documented limits, and documentation that lets someone else verify your results
• Build analytical features and datasets from large, messy, document-heavy corpora, including text extracted with Amazon Textract and analyzed with foundation models through Amazon Bedrock
• Harden one-off notebooks into repeatable, reviewed analytical pipelines
• Put findings in front of decision-makers in plain language, with visuals that carry the argument instead of decorating it
• Use artificial intelligence (AI)-assisted analysis as standard practice, with language models and coding assistants across the lifecycle and your judgment on top

Skills

• The initial engagement requires United States citizenship and the ability to obtain a Public Trust determination
• A working command of statistics and machine learning applied to real operational data, not just curated coursework sets
• The engineering habits that make analysis trustworthy: version control, reproducible pipelines, tested transformations, and documentation someone else can follow
• The communication craft to make a technical result understandable to the people who depend on it
• The precision to work where accuracy and auditability are not optional
• 4+ years of applied data science or statistical modeling experience
• Bachelor's degree
• Strong working command of Python and SQL
• Working knowledge of statistics, machine learning, and model validation
• Familiarity with cloud-based data and analytics services on AWS
• Ability to carry an analysis from question to defensible, documented answer
• Proficiency in writing, PowerPoint, and Excel
• This is a remote position, although a hybrid arrangement based in the Washington, DC metropolitan area with openness to a variable commuting cadence is preferred
• Master's degree in a relevant field
• Experience with modern data tools and platforms (Amazon Aurora, Amazon Simple Storage Service (S3) with Apache Iceberg, AWS Glue, or Trino)
• Experience applying large language models to analytical work (Amazon Bedrock or comparable services)
• Data-visualization craft, from chart design through dashboards and charting libraries
• Federal information technology experience
• Familiarity with AI-assisted developer tooling

Qualifications

Must Haves

• The initial engagement requires United States citizenship and the ability to obtain a Public Trust determination
• A working command of statistics and machine learning applied to real operational data, not just curated coursework sets
• The engineering habits that make analysis trustworthy: version control, reproducible pipelines, tested transformations, and documentation someone else can follow
• The communication craft to make a technical result understandable to the people who depend on it
• The precision to work where accuracy and auditability are not optional
• 4+ years of applied data science or statistical modeling experience
• Bachelor's degree
• Strong working command of Python and SQL
• Working knowledge of statistics, machine learning, and model validation
• Familiarity with cloud-based data and analytics services on AWS
• Ability to carry an analysis from question to defensible, documented answer
• Proficiency in writing, PowerPoint, and Excel

Nice to Haves

• This is a remote position, although a hybrid arrangement based in the Washington, DC metropolitan area with openness to a variable commuting cadence is preferred
• Master's degree in a relevant field
• Experience with modern data tools and platforms (Amazon Aurora, Amazon Simple Storage Service (S3) with Apache Iceberg, AWS Glue, or Trino)
• Experience applying large language models to analytical work (Amazon Bedrock or comparable services)
• Data-visualization craft, from chart design through dashboards and charting libraries
• Federal information technology experience
• Familiarity with AI-assisted developer tooling

Benefits

• Remote position, with a preferred hybrid arrangement based in the Washington, DC metropolitan area and openness to a variable commuting cadence.
• Extensive onboarding.
• Sponsored professional certifications such as the Data Management Capability Assessment Model (DCAM) and AWS technical certifications.
• Rotation across functions to expand your skills and perspective.
• Medical, dental, and vision insurance with the employee premium fully paid and half of dependent premiums.
• Employer-paid life, accidental death, and short-term and long-term disability insurance.
• A 401(k) matched 100% up to 4% of salary, vesting immediately.
• Unlimited paid time off.
• Sponsored professional certifications and continuing education.