Biostatistician

General Dynamics Information Technology•San Diego, CA

1d•$63,312 - $85,658•Onsite

About The Position

We are GDIT. The people supporting and securing some of the most complex government, defense, and intelligence projects across the country. We ensure today is safe and tomorrow is smarter. Our work has meaning and impact on the world around us, but also on us, and that’s important. GDIT is your place. You make it your own by embracing autonomy, seizing opportunity, and being rusted to deliver your best every day. We think. We act. We deliver. There is no challenge we can’t turn into opportunity. And our work depends on a Biostatistician joining our team to support customer activities. The Biostatistician leads analytical, statistical, and data engineering efforts to support readiness, human performance, and enterprise decision‑making. This role designs, develops, and deploys advanced analytics solutions, including predictive modeling, machine learning, and data integration workflows. The Biostatistician transforms complex, structured, semi‑structured, and unstructured data into actionable insights and mission‑relevant intelligence. This position partners with interdisciplinary teams across operations, intelligence, technology, and human performance to deliver high‑quality analytical products and support data‑driven program evaluation.

Requirements

Master’s or doctoral degree with (5) years’ experience in quantitative science, social science or related discipline.
Strong proficiency in Python or R for analytics, ML, and data manipulation, with disciplined software practices (modular code, testing mindset, version control).
Advanced SQL skills and hands-on experience with SQL Server in applied analytics and data preparation contexts.
Demonstrated experience using Databricks and Apache Spark (PySpark) or comparable experience, to build scalable data pipelines and large-scale transformations.
Solid understanding of data engineering concepts: ETL/ELT design, data modeling fundamentals, data quality and validation, repeatable pipeline design, and performance optimization.
Experience producing decision-quality visualization and reporting, preferably with Power BI (including semantic modeling and DAX familiarity).
Familiarity with NLP, LLMs, and agent concepts, including how to prepare and govern data for these workflows and how to evaluate outcomes.
Experience integrating analytics into applications and automations using Power Apps (Canvas/Model-Driven) and Power Automate beyond basic usage.
Experience with web application development technologies: HTML, CSS, JavaScript, React, and backend frameworks such as Django or ASP.NET Core.
Exposure to operationalizing models and pipelines (scheduling/orchestration, monitoring/alerting, CI/CD concepts, logging and traceability).
Proficient with the suite of Microsoft Office programs, including Word, Excel and Access.
Advanced proficiency may be demonstrated through an employment history in academia or other setting where the conduct of research is routine.
Proficiency shall be further demonstrated by a history of scientific publications.
Have at least three (3) years of research experience in academic, social services, government, healthcare or laboratory setting.
Secret or Top-Secret Clearance, or the ability to obtain clearance.

Nice To Haves

Analytics
Datasource
Data Transformation
Structured Query Language (SQL)

Responsibilities

Lead end-to-end analytics initiatives from problem framing and experimental design through production delivery, measurement, and iterative improvement.
Architect and implement scalable data solutions by building and maintaining ETL/ELT pipelines and curated datasets using SQL Server, Databricks, and Apache Spark (PySpark) or comparable structures.
Fuse disparate structured, semi-structured, and unstructured data sources; establish data preparation standards, reusable transformations, and documented assumptions to ensure mission defensibility and reproducibility.
Implement data quality controls (validation rules, anomaly detection, reconciliation checks), manage schema changes, and optimize Spark workloads for performance, reliability, and cost (e.g., efficient joins, partitioning strategies, job tuning).
Develop, evaluate, and deploy predictive models and optimization approaches; communicate model behavior, limitations, and expected impact to both technical teams and operational stakeholders.
Support text-heavy and unstructured-data use cases with NLP methods (cleaning, normalization, entity extraction/labeling as applicable) and demonstrate working familiarity with Large Language Models and agent-style workflows (prompting patterns, retrieval-style approaches, evaluation datasets, and feedback loops).
Deliver decision-support products through Power BI, including semantic modeling and consistent metric definitions, and enable operational workflows and user- facing tools using the Power Platform (Power Apps—Canvas and Model-Driven— and Power Automate).
Provide technical leadership and consultation: guide analytic methodology, review code and results, ensure documentation standards, and collaborate with intelligence, operations, and engineering teams to uncover novel solutions to complex command challenges.
Responsible for entering, cleaning, and conducting advanced data manipulation and statistical analysis.
Operating in consultation with POTFF program staff, Junior and Senior Biostatisticians, and USSOCOM Enterprise Data Team, the Biostatistician shall provide subject matter expertise in the areas of program evaluation, research methodologies and data analysis.
Provide consultation and assistance to supported units and POTFF staff to identify opportunities and methods for capturing data relating to POTFF programs and initiatives
Prepare reports and presentations that accurately convey data trends and associated analyses.
Will be granted access to Government systems to enter and analyze data.