Data Scientist

MANTECH; Aiea (HI); On-site; USD 120,000 - 140,000; Full time

Job summary

A leading defense analytics company seeks a mission-driven Data Scientist in Oahu, Hawaii, to support advanced analytics and machine learning efforts. The role includes designing predictive models and translating data into actionable insights for mission-critical decisions. Candidates should have 9+ years of experience with a Bachelor's degree in a related field, proficiency in Python or R, and knowledge of machine learning frameworks. An active TS/SCI clearance is required for this position.

Qualifications

• 9+ years of relevant experience, including 4+ years leading data science initiatives.
• Proficiency in statistical analysis and model development languages.
• Experience with machine learning frameworks.

Responsibilities

• Design and deploy predictive models and data pipelines.
• Translate data into actionable intelligence for planning.
• Leverage AI/ML technologies to build models for command objectives.

Skills

Python

Machine Learning

Data Analysis

Data Visualization

SQL

Education

Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or related field

Tools

TensorFlow

PyTorch

Scikit-learn

AWS

Docker

Job description

Overview

MANTECH seeks a mission-driven and innovative Data Scientist to join our team in Oahu, Hawaii. In this role you will support cutting-edge analytics, machine learning, and data engineering techniques to deliver strategic and tactical insights that enhance readiness, agility, and operational effectiveness. This role directly supports national defense priorities and partners with key mission stakeholders.

Responsibilities

• Design and deploy predictive models, data pipelines, and statistical analyses to inform mission decisions.
• Translate data into actionable intelligence for both technical and non-technical audiences, contributing to strategic and operational planning.
• Leverage AI/ML technologies to build models that support command objectives, including readiness assessments, resource optimization, and mission planning.
• Collaborate with multi-functional teams including data engineers, logisticians, and operations planners to deploy and refine ML models using Government MLOps platforms.
• Develop advanced data visualizations to enhance situational awareness and enable faster, informed decision-making in distributed environments.
• Document methodologies and processes to ensure reproducibility, knowledge sharing, and seamless transition across analytic teams.
• Support the integration of mission-enabling technologies including robotic process automation (RPA), natural language processing, and predictive analytics.

Minimum Qualifications

• Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or related field
• 9+ years of relevant experience, including 4+ years leading data science initiatives and developing predictive models
• Proficiency in Python, R, or similar languages for statistical analysis and model development
• Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn
• Skilled in data querying using SQL/NoSQL and working within cloud environments (AWS, Azure, or GCP)
• High School and 4 years of additional experience or Associate's Degree and 2 years of additional experience may be exchanged in lieu of a required Bachelor's degree

Preferred Qualifications

• Master’s or Ph.D. in a quantitative discipline
• Experience supporting Department of Defense and/or Intelligence Community missions
• Familiarity with geospatial tools such as ArcGIS or QGIS
• Experience with containerization (e.g., Docker) and DevSecOps pipelines
• Working knowledge of Agile development methodologies and Git-based version control

Clearance Requirements

• Must hold an Active TS/SCI clearance.

Physical Requirements

• The person in this position must be able to remain in a stationary position 50% of the time.
• Occasionally move about inside the office to access file cabinets, office machinery, or to communicate with co-workers, management, and customers, via email, phone, and or virtual communication, which may involve delivering presentations.