About this opportunity
American Bureau of Shipping (ABS) lists this Data Scientist opportunity in washington, District of Columbia. Review the employer’s description below for duties, qualifications and application requirements.
Job description
ABS is seeking a Data Scientist to join its Artificial Intelligence Practice, supporting a major federal modernization program. The role focuses on applying machine learning, statistical analysis, and modern AI techniques to large datasets in support of mission-critical planning and operations.
Responsibilities
Analyze large and complex datasets using statistical methods, machine learning, and AI techniques
Build, test, and maintain predictive models and analytical workflows
Apply methods including machine learning, deep learning, NLP, generative AI, large language models, and time series analysis to mission-focused data problems
Support feature engineering, data preparation, model evaluation, and reproducible analytical development
Assist with transitioning analytics and machine learning capabilities from pilot efforts into production environments
Contribute to synthetic data development and other advanced analytical methods when appropriate
Partner with engineers and stakeholders to translate business needs into practical analytical solutions
Prepare technical documentation, reports, presentations, and other project deliverables
Support responsible AI practices, including explainability, trustworthiness, and AI risk management
Required Qualifications
Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related STEM field
Relevant professional experience applying data science, machine learning, or advanced analytics; depth and scope will vary based on the level filled
Experience working with large, real-world datasets across the full analytical lifecycle
Proficiency in Python and working knowledge of SQL
Experience with machine learning, predictive modeling, model evaluation, and feature engineering
Familiarity with NLP, GenAI, and LLM methods
Familiarity with deep learning, neural networks, anomaly detection, and time series methods
Strong communication skills, including the ability to clearly explain technical findings to varied audiences
Ability to develop reproducible analytical workflows and clear technical documentation
Preferred Qualifications
Master’s degree
Experience supporting production or operational deployment of analytical or machine learning solutions
Experience in a federal, public sector, or regulated data environment
Familiarity with survey, demographic, statistical, or population-scale data
Exposure to record linkage, entity resolution, or matching models
Experience with synthetic data, differential privacy, or responsible AI practices
Technologies
Python
SQL
NLP
GenAI
LLM
Deep learning
Neural networks
Anomaly detection
Time series analysis
Large language models
Career Level and Compensation
This position may be filled at multiple career levels based on business need and the selected candidate’s qualifications, relevant experience, and demonstrated capability. Typical leveling is as follows: Junior (0 to 4 years), Mid-Level (5 to 9 years), Senior (10 to 14 years), Principal (15 or more years). These ranges are guidelines only and are not the sole determining factor in level.
The posted compensation range reflects the full range across all possible levels. Individual offers will be based on the level at which the candidate is hired and factors such as skills, experience, internal equity, and geographic market considerations where applicable.
Reporting Relationships
Reports directly to the Chief Data Scientist or a Manager, Director, or Executive role.
Location and Work Arrangement
Based in the Washington, D.C. metro area, with primary work performed in Suitland, Maryland. Remote or hybrid arrangements may be available for eligible work, subject to government approval.
#J-18808-Ljbffr
Worksite address
washington, DC, 20022, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.