Associate Data Scientist

Norfolk, VAHybridFull TimeEntry-level (exp-based)Posted 1 month agoVisa sponsorship available

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Required skills

Python
Pandas
NumPy
Scikit-learn
SciPy
regression analysis
probability distributions
hypothesis testing
simulation
Bayesian modeling

Nice to have

Qlik
Tableau
Python-based visualization packages
Databricks
Apache Spark

Role summary

FTI is seeking an Associate Data Scientist for the Naval Safety Command in Norfolk, VA. This hybrid role involves developing, testing, and deploying advanced predictive analytics models to diagnose and predict naval mishap precursors. Responsibilities include designing risk models, extracting insights from data using various statistical and machine learning techniques, supporting feature engineering, and collaborating with software engineers. A DoD Secret Clearance is required. The ideal candidate will have a Bachelor's degree in a related field, 1-2 years of data science experience, and proficiency in Python or R with experience in analytical toolkits.

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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