Job Requirements
Remote Norfolk, VA
Secret Polygraph Unspecified
Early Career (2+ yrs experience)
Salary not specified
Join Premium to unlock estimated salaries 
Job Description
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
#LI-EB1
#LI-Onsite
group id: 10240918
FTI - Intro Video
