Data Scientist

Data ScientistThe Data Scientist applies statistical analysis, data mining, and machine learning to human performance, behavioral health, and readiness data to produce actionable insights, forecasts, and decision-support products for the POTFF enterprise. The Data Scientist frames analytical questions with Government stakeholders, prepares and explores data, selects and applies appropriate methods, validates results, and communicates findings to technical and non-technical audiences through reports, briefings, and visual analytics built on the Government-furnished technology stack.HOW DATA SCIENTIST WILL MAKE AN IMPACT:Query, clean, transform, and prepare data from the Government-designated Human Performance System of Record (e.g., HPDMS) and other Government-approved sources for analysis, using the curated datasets maintained by the Data Engineer where available.Develop, validate, and document predictive and prescriptive models, forecasting methods, clustering, and other advanced statistical techniques to generate actionable forecasts regarding operator readiness, injury risk, program efficacy, and performance optimization, as directed by the Government.Support text-heavy use cases using Natural Language Processing (NLP) techniques (e.g., cleaning, entity extraction, classification) to analyze unstructured clinical or survey data and apply Large Language Model (LLM) and agent-style workflows only within Government-approved tools and datasets.Develop, deploy, and maintain visual analytics, dashboards, and executive reports using Government-furnished tools (e.g., Power BI, including semantic modeling and DAX), and integrate data products into low-code operational workflows (e.g., Microsoft Power Platform) where directed.Support Government-designed analyses and experiments that measure the validity, efficacy, and Return on Investment (ROI) of POTFF interventions, including computation of program-efficacy metrics as directed by the Government.Automate recurring analyses and the generation of required monthly and quarterly reports, reducing manual effort and improving accuracy.Document data sources, transformations, assumptions, methods, and validation procedures so that analyses are reproducible and can be transferred to other personnel.Communicate complex concepts, methods, and results clearly to non-technical command leadership and to clinical and performance staff, in writing and in briefings.Collaborate with embedded clinical and performance staff to identify opportunities for capturing data and improving the quality of input into Government systems.Maintain rigorous data quality, security, and privacy controls, including DoW Impact Level 5 (IL5), HIPAA, and Privacy Act protocols, in all analytic work.WHAT YOU'LL NEED TO SUCCEED:Bachelor's degree in a quantitative discipline, including but not limited to statistics, biostatistics, mathematics, applied mathematics, data science, operations research, computer science, engineering, physics, economics or economics, epidemiology, geospatial science or geoinformatics, or psychology or another behavioral science with a quantitative-methods concentration, with documented coursework or professional application in statistics, programming, and quantitative analysis.Minimum of one (1) year of experience applying data science or statistical methods to real-world problems. A Bachelor's degree program that included documented internship, cooperative-education, capstone, thesis, or project work applying data science methods to real-world data satisfies this requirement.Demonstrated proficiency in Python or R for data analysis, statistical modeling, and machine learning, and in SQL for querying relational data, demonstrated through professional work experience or degree-program projects.Working knowledge of applied statistics and of supervised and unsupervised machine-learning methods.Ability to prepare and clean data for analysis, including familiarity with data engineering concepts (ETL/ELT, data modeling basics, reproducible workflows, and version control with Git).Experience producing visual analytics and reports for decision-makers (Power BI preferred).Ability to communicate clearly with stakeholders and translate mission needs into analytical questions and outputs.PREFERRED QUALIFICATIONS:Experience with Databricks and Apache Spark (PySpark) or a comparable distributed processing system.Familiarity with NLP and LLM use cases, including text preparation, evaluation datasets, and governance considerations.Familiarity with the Microsoft Power Platform (Power Apps and Power Automate) and with Palantir Foundry.Experience with web application development technologies (e.g., HTML, CSS, JavaScript, React, Django, or ASP.NET Core) or with deploying analytics into applications. Software engineering or web-development experience is not required.Experience with human performance, sports science, health, clinical, or biomedical data.LOCATION: Various CONUS SITESCLEARANCE: Secret or Top-Secret Clearance, or the ability to obtain clearance.This is a contingent posting, expected to start in 2027.GDIT IS YOUR PLACE:401K with company matchComprehensive health and wellness packagesInternal mobility team dedicated to helping you own your careerProfessional growth opportunities including paid education and certificationsCutting-edge technology you can learn fromRest and recharge with paid vacation and holidaysThe likely salary range for this position is $80,179 - $108,477. This is not, however, a guarantee of compensation or salary. Rather, salary will be set based on experience, geographic location and possibly contractual requirements and could fall outside of this range.