Data Scientist

ABS Group is seeking a Data Scientist to join our Artificial Intelligence Practice in support of a major federal modernization program. In this role, you will apply machine learning, statistical analysis, and modern AI techniques to large, complex datasets that support mission-critical planning and operations.

You will work alongside data scientists, engineers, and client stakeholders to build analytical solutions that improve data quality, support decision-making, and help move advanced analytics from prototype to operational use. The scope of responsibility, degree of technical leadership, and level of independence expected will reflect the level at which this position is filled.

What You Will Do:

Analyze large and complex datasets using statistical methods, machine learning, and AI techniques

Build, test, and maintain predictive models and analytical workflows

Apply methods such as 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

Help transition analytics and machine learning capabilities from pilot efforts into production environments

Contribute to synthetic data development and other advanced analytical methods where 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

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What You Will Need:

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 for this role 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, as well as factors such as skills, experience, internal equity, and geographic market considerations where applicable.

Education and Experience

Bachelor''s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related STEM field; Master''s degree preferred

Relevant professional experience applying data science, machine learning, or advanced analytics; the depth and scope of experience required will vary based on the level at which this position is filled

Experience working with large, real-world datasets across the full analytical lifecycle preferred

Experience supporting production or operational deployment of analytical or machine learning solutions a plus

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Knowledge, Skills, and Abilities

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 explain technical findings clearly to varied audiences

Ability to develop reproducible analytical workflows and clear technical documentation

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Nice to Have:

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

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Reporting Relationships:

Reports directly to the Chief Data Scientist or a Manager, Director, or Executive role.

Location

This position is 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.