Senior Data Scientist, Machine Learning

General Dynamics

Confirmed live 2 days ago High trust
Remote

Quick summary

Work type
Remote
Location
Remote
Salary
$123,250–$166,750 / yr
Posted
27 days ago
Freshness
Confirmed live 2 days ago

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $195k
This role $145k
$111k most similar roles pay here $242k

This role pays less than 82% of similar roles. Most pay $162,000–$228,987 — the shaded band above. At the midpoint, this role pays about $145k versus about $195k for comparable roles.

Based on 240 similar postings.

Employer

About General Dynamics

General Dynamics is a global aerospace and defense company offering a broad portfolio of products and services in business aviation, ship construction, land combat vehicles, and information technology. It serves customers in the U.S. government, allied governments, and a diverse array of commercial markets.

General Dynamics currently has 1123 open roles on FindRole.

Listed pay typically runs $124,093–$150,385 across 984 roles with salary data.

Most-posted roles

View all roles at General Dynamics

At a glance

TL;DR · Senior Data Scientist, Machine Learning

As the Senior Data Scientist - Machine Learning for the Healthcare Fraud Prevention Partnership, you will serve as the first dedicated machine learning practitioner within a specialized fraud, waste, and abuse analytics program. You will build predictive models against a multi-billion record claims warehouse to identify fraudulent billing patterns and establish the foundational practices for moving models into production. Your daily work involves designing, training, and validating supervised models using Python and SQL while performing large-scale feature engineering. You will also manage model deployment, versioning, and drift monitoring. The role requires expertise in healthcare claims data, including coding systems like ICD-10 and CPT. Key technical skills include Amazon Web Services (AWS), predictive modeling, and handling extreme class imbalance. You will collaborate with subject matter experts to translate complex findings into actionable evidence for investigators.

What does a Data Scientist earn in Remote?

Median $217225 from 40 postings across 18 companies.

See salary data

What you'll do

  • Design, train, and validate supervised models to identify fraud, waste, and abuse in healthcare claims.
  • Perform large-scale feature engineering on billions of records using Python and SQL within a data warehouse.
  • Establish the standard processes for moving machine learning models from development into production environments.
  • Monitor model health through scheduled execution, versioning, and drift monitoring.
  • Provide human-readable rationales and evidence to support investigator actions based on model scores.
  • Collaborate with subject matter experts to distinguish genuine anomalies from policy-driven patterns.
  • Communicate technical methodologies and model limitations to non-technical stakeholders and partners.

What we're looking for

  • Master's degree in a quantitative field or a Bachelor's with equivalent hands-on experience.
  • 5+ years of experience building, validating, and delivering supervised machine learning models on real-world data.
  • Experience deploying models into production including scheduling, versioning, and drift monitoring.
  • Proficiency in Python and SQL for large-scale feature engineering within a data warehouse.
  • 2+ years of experience working with healthcare claims data and coding systems like ICD-10 or CPT.
  • Ability to explain model outputs to non-technical audiences and defend methodologies to technical stakeholders.
  • Experience with validation design for imbalanced, temporally shifting problems including leakage detection and calibration.
  • Graph analytics, entity resolution, and modeling in regulated settings (preferred); AWS/Snowflake experience (preferred).

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