Biostatistician

General Dynamics

Confirmed live today High trust

Quick summary

Work type
On-site
Location
Fort Bragg, NCSan Diego, CAHurlburt Field, FLFort Campbell, KYJoint Base Lewis-McChord, WA
Salary
$63,312–$85,658 / yr
Posted
117 days ago
Freshness
Confirmed live today
Nearby
16 roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $159k
This role $74k
$47k $212k
below market most similar roles pay here above market

This role pays less than 99% of similar roles. Most pay $126,800–$191,500 — the blue band above. At the midpoint, this role pays about $74k versus about $159k 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 1377 open roles on FindRole.

Listed pay typically runs $124,093–$150,385 across 1184 roles with salary data.

Most-posted roles

View all roles at General Dynamics

At a glance

TL;DR · Biostatistician

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The Biostatistician joins the Data Science and Data Engineering team to lead analytical, statistical, and data engineering efforts supporting readiness, human performance, and enterprise decision-making. This role involves designing and deploying advanced analytics solutions, including predictive modeling, machine learning, and data integration workflows. The Biostatistician transforms complex structured and unstructured data into actionable intelligence by building ETL/ELT pipelines and curated datasets. Key technologies include SQL Server, Databricks, Apache Spark (PySpark), Python, and R. Candidates will also utilize Power BI, Power Apps, and Power Automate for decision-support products. Core competencies include NLP methods, Large Language Models, and data quality controls. The role solves complex command challenges by providing subject matter expertise in program evaluation and research methodologies to support mission-relevant intelligence and data-driven program evaluation.

Skills

SQL Python R Databricks Apache Spark PySpark SQL Server Power BI Power Platform Power Apps Power Automate NLP LLMs ETL ELT CI/CD HTML CSS JavaScript React Django ASP.NET Core Machine Learning Predictive Modeling

What you'll do

  • Lead end-to-end analytics initiatives from problem framing and experimental design through production delivery.
  • Architect and maintain scalable ETL/ELT pipelines using SQL Server, Databricks, and Apache Spark.
  • Fuse disparate structured and unstructured data sources while establishing data preparation standards and quality controls.
  • Develop and deploy predictive models and optimization approaches to support enterprise decision-making.
  • Apply NLP methods and Large Language Models to process and normalize text-heavy and unstructured data.
  • Deliver decision-support products and semantic models using Power BI and the Power Platform.
  • Provide technical leadership by reviewing code, guiding analytic methodologies, and ensuring documentation standards.
  • Prepare reports and presentations that accurately convey data trends and associated statistical analyses.

What we're looking for

  • Must possess a Master's or doctoral degree in a quantitative science, social science, or related discipline.
  • Must have 5+ years of related experience.
  • Must have research experience in academic, social services, government, healthcare, or laboratory settings.
  • Must be a US Citizen.
  • Must currently possess a Top Secret clearance or be able to obtain one.
  • Must have strong proficiency in Python or R for analytics, machine learning, and data manipulation.
  • Must have advanced SQL skills and hands-on experience with SQL Server in applied analytics and data preparation contexts.
  • Must have demonstrated experience using Databricks and Apache Spark (PySpark) to build scalable data pipelines.

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