Associate Data Scientist

Frontier Technology Inc.; Norfolk (VA); Hybrid; USD 70,000 - 95,000; Full time

Job summary

Frontier Technology Inc. is seeking an Associate Data Scientist to support the Naval Safety Command in Norfolk, VA.

You will collaborate with data scientists and software engineers on the development, testing, and deployment of predictive analytics models to diagnose and predict precursors to naval mishaps and safety hazards. The role is hybrid with on-site work at the Naval Safety Command Center in Norfolk, VA and requires a DoD Secret Clearance.

Qualifications

• Active DoD Secret Clearance.
• Bachelor's Degree in Data Science, Statistics, Mathematics, Computer Science, Operations Research, or a related field.
• 1-2 years of practical data science/analytics experience (or a Master's degree with substantive applied research/project experience).
• Proficiency in Python or R, or a similar language
• Practical experience with Pandas, NumPy, Scikit-learn, SciPy, or related packages.
• Foundational understanding of regression analysis, probability distributions, hypothesis testing, and simulation or Bayesian modeling techniques.

Responsibilities

• Support in the designing, calibrating, and testing of a portfolio of predictive risk models to evaluate mishap risk for individual Navy communities.
• Support analytical focus on extracting insights from data to make predictions, understand relations, and identify unusual patterns using time series/forecasting, causal inference, statistical modeling, and anomaly detection.
• Support feature engineering, cross-validation, and creation of performance metrics (precision, recall) to minimize error and eliminate overfitting.
• Partner with software engineers and senior data scientists to integrate features and transition analytical models into operational environments.
• Participate in technical exchange meetings and assist in training personnel on model maintenance and interpretation.

Skills

Python

R

Pandas

NumPy

Scikit-learn

SciPy

Regression analysis

Probability distributions

Hypothesis testing

Bayesian modeling

Education

Bachelor's degree in Data Science/Statistics/Math/CS

Tools

Databricks

Apache Spark

Tableau

Qlik

Job description

Associate Data Scientist

Job ID: 2026-7083

Category: Engineering

Type: Regular Full-Time

Location: US-VA-Norfolk

Telecommute: Yes

Clearance Requirements: Secret

Overview

FTI is hiring an associate Data Scientist to support the Naval Safety Command in Norfolk, VA. As a member of the data science team, you will be working with a team of Data Scientists and Software Engineers to support the development, testing, and deployment of a series of advanced predictive analytics models using data sets that will help diagnose and predict precursors to Naval mishaps and safety hazards.

This is a hybrid position with an on-site at the Naval Safety Command Center in Norfolk, VA. A DoD Secret Clearance is required for this position.

Responsibilities

• Support in the designing, calibrating, and testing of a portfolio of predictive risk models to evaluate mishap risk for individual Navy communities.
• Support analytical focus on extracting insights from data to make predictions, understand relations, and identify unusual patterns using approaches like time series/forecasting, causal inference, statistical modeling, and anomaly detection.
• Support feature engineering, cross-validation, and creation of performance metrics (precision, recall) to minimize error and eliminate overfitting.
• Partner with software engineers and senior data scientists to integrate features and transition analytical models into operational environments.
• Participate in technical exchange meetings and assist in training personnel on model maintenance and interpretation.

Education/Qualifications

Required:

• Active Department of Defense (DoD) Secret Clearance
• Bachelor's Degree in Data Science, Statistics, Mathematics, Computer Science, Operations Research, or a related field.
• 1-2 years of practical data science/analytics experience (or a Master's degree with substantive applied research/project experience).
• Proficiency in Python or R, or a similar language
• Practical experience with analytical and machine learning toolkits, such as Pandas, NumPy, Scikit-learn, SciPy, or related packages.
• Foundational understanding of regression analysis, probability distributions, hypothesis testing, and simulation or Bayesian modeling techniques.

Preferred:

• Ability to develop data visualizations and functional dashboards in Qlik, Tableau, or Python-based visualization packages.
• Exposure to Databricks or Apache Spark

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