Posted today
Top Secret/SCI
Early Career (2+ yrs experience)
Unspecified
CI Polygraph
IT - Data Science
Herndon, VA (On/Off-Site)
Data Scientist
About the Team
Here at BTI360, we’ve built a culture that’s passionate about developing software engineers. Software doesn't build itself. People do. In fact, teams of people do. That's why our primary focus is on developing better craftsmen, better teammates, and better technical leaders. By putting people first, we're not just giving our teammates more opportunities to grow, we're also raising the bar of the software we ship. BTI360 previously has been voted 10 years in a row as a TOP Place to Work by the Washington Business Journal.
BTI360 is seeking a Data Scientist who is passionate about transforming raw data into meaningful insights that drive strategic decision‑making. In this role, you’ll work closely with our engineers and mission teams to tackle complex business problems using machine learning and emerging AI technologies.
You’ll thrive here if you are naturally curious, driven to ask the right questions, and energized by turning complexity into clarity. Our data scientists don’t just build models, they influence decisions, shape strategy, and help our customers navigate high‑impact mission challenges.
What you will do in this role:
As a Data Scientist at BTI360, you will:
• Lead end-to-end machine learning projects from problem definition to production, leveraging pre-trained models and LLMs for rapid prototyping, then using data-driven evaluation to determine when to invest in custom solutions such as fine-tuned models or purpose-built small language models.
• Design and conduct rigorous model evaluations using industry-standard methodologies, including developing custom evaluation frameworks for clustering, classification, embeddings, and entity resolution systems.
• Translate business requirements into quantitative problems and communicate technical findings to both technical and non-technical stakeholders through reports, presentations, and direct customer engagement.
• Drive technical decision-making for model selection, including evaluating embeddings models, LLMs, and other ML systems against business requirements and performance benchmarks.
• Optimize existing systems by identifying data quality issues, implementing performance improvements, and developing novel approaches that deliver measurable improvements in key metrics.
• Stay current with ML advances and introduce new techniques and frameworks to the team, including participating in or presenting at industry conferences
• Apply statistical methods to validate findings and support data‑driven decisions.
• Develop reports and whitepapers that evaluate solution alternatives based on impact, cost, technical feasibility, and alignment with strategic goals.
• Senior candidates will also need to: Collaborate across teams to align on strategy, provide data science expertise, and contribute to proposals and strategic initiatives.
• Senior candidates will also need to: Mentor junior data scientists by providing technical guidance, defining project direction, and sharing best practices in model development and evaluation.
You may thrive in this role if you have the following skills:
• Active TS/SCI with Polygraph
• 3+ years of experience in data science or machine learning roles with demonstrated impact on production systems.
• Deep expertise in NLP and modern ML techniques including embeddings, clustering, classification, and working with LLMs.
• NLP experience including feature engineering and modeling for text data.
• Knowledge of ML evaluation metrics appropriate for various use cases.
• Proven track record of model evaluation using appropriate metrics and methodologies for different problem types (precision/recall, silhouette scores, benchmarks, etc.).
• Strong scripting skills with experience in AI/ML frameworks (scikit-learn, PyTorch/TensorFlow, transformers) and data manipulation libraries, including proficiency with Jupyter notebooks for exploratory analysis and experimentation.
• Basic software engineering practices such as git, CI/CD, code reviews, documentation, and ability to access and leverage remote APIs.
• Familiarity with cloud platforms (AWS, Azure, GCP).
• Excellent communication skills with experience translating technical metrics into business value and presenting findings to leadership and customers.
• Ability to work independently
You may excel in this role if you have the following skills:
• Strong Python programming skills
• Experience integrating ML models into production systems.
• Experience customizing or fine‑tuning LLMs (LoRA, distillation, etc.).
• Experience with large or multimodal datasets.
• Proficiency in SQL and Elasticsearch/Elastic Stack for building evaluation datasets and querying production data systems.
• Experience leading technical initiatives
About the Team
Here at BTI360, we’ve built a culture that’s passionate about developing software engineers. Software doesn't build itself. People do. In fact, teams of people do. That's why our primary focus is on developing better craftsmen, better teammates, and better technical leaders. By putting people first, we're not just giving our teammates more opportunities to grow, we're also raising the bar of the software we ship. BTI360 previously has been voted 10 years in a row as a TOP Place to Work by the Washington Business Journal.
BTI360 is seeking a Data Scientist who is passionate about transforming raw data into meaningful insights that drive strategic decision‑making. In this role, you’ll work closely with our engineers and mission teams to tackle complex business problems using machine learning and emerging AI technologies.
You’ll thrive here if you are naturally curious, driven to ask the right questions, and energized by turning complexity into clarity. Our data scientists don’t just build models, they influence decisions, shape strategy, and help our customers navigate high‑impact mission challenges.
What you will do in this role:
As a Data Scientist at BTI360, you will:
• Lead end-to-end machine learning projects from problem definition to production, leveraging pre-trained models and LLMs for rapid prototyping, then using data-driven evaluation to determine when to invest in custom solutions such as fine-tuned models or purpose-built small language models.
• Design and conduct rigorous model evaluations using industry-standard methodologies, including developing custom evaluation frameworks for clustering, classification, embeddings, and entity resolution systems.
• Translate business requirements into quantitative problems and communicate technical findings to both technical and non-technical stakeholders through reports, presentations, and direct customer engagement.
• Drive technical decision-making for model selection, including evaluating embeddings models, LLMs, and other ML systems against business requirements and performance benchmarks.
• Optimize existing systems by identifying data quality issues, implementing performance improvements, and developing novel approaches that deliver measurable improvements in key metrics.
• Stay current with ML advances and introduce new techniques and frameworks to the team, including participating in or presenting at industry conferences
• Apply statistical methods to validate findings and support data‑driven decisions.
• Develop reports and whitepapers that evaluate solution alternatives based on impact, cost, technical feasibility, and alignment with strategic goals.
• Senior candidates will also need to: Collaborate across teams to align on strategy, provide data science expertise, and contribute to proposals and strategic initiatives.
• Senior candidates will also need to: Mentor junior data scientists by providing technical guidance, defining project direction, and sharing best practices in model development and evaluation.
You may thrive in this role if you have the following skills:
• Active TS/SCI with Polygraph
• 3+ years of experience in data science or machine learning roles with demonstrated impact on production systems.
• Deep expertise in NLP and modern ML techniques including embeddings, clustering, classification, and working with LLMs.
• NLP experience including feature engineering and modeling for text data.
• Knowledge of ML evaluation metrics appropriate for various use cases.
• Proven track record of model evaluation using appropriate metrics and methodologies for different problem types (precision/recall, silhouette scores, benchmarks, etc.).
• Strong scripting skills with experience in AI/ML frameworks (scikit-learn, PyTorch/TensorFlow, transformers) and data manipulation libraries, including proficiency with Jupyter notebooks for exploratory analysis and experimentation.
• Basic software engineering practices such as git, CI/CD, code reviews, documentation, and ability to access and leverage remote APIs.
• Familiarity with cloud platforms (AWS, Azure, GCP).
• Excellent communication skills with experience translating technical metrics into business value and presenting findings to leadership and customers.
• Ability to work independently
You may excel in this role if you have the following skills:
• Strong Python programming skills
• Experience integrating ML models into production systems.
• Experience customizing or fine‑tuning LLMs (LoRA, distillation, etc.).
• Experience with large or multimodal datasets.
• Proficiency in SQL and Elasticsearch/Elastic Stack for building evaluation datasets and querying production data systems.
• Experience leading technical initiatives
group id: 90798301
