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Data Scientist with Security Clearance
Kruger RecruitingWashington, DC🇺🇸United StatesPosted 12 Jul 2026
Quick Overview
Work Type
Hybrid
Schedule
Employee
Level
Mid Senior
Job Description
We are seeking a Senior Data Scientist with a strong sense of ownership to join our Platform team. This position has career growth opportunities for those seeking to become Lead Data Scientist and/or Team Manager. As a Data Scientist, you will
Use the capabilities of our AI Platform to deploy production solutions for our customers.
Work with customer data and own the development of an AI solution from ideation to production
Leverage integrations with big data frameworks (e.g. Databricks) as needed to develop solutions for customers. Primary Focus: Exploratory data analysis, model selection, feature engineering, hyperparameter tuning, setting up backtesting/evaluation frameworks, and some data engineering and SWE tasks Technical Skills: Foundational knowledge in data science/ML/CS Core Strengths: Choosing appropriate models, analyzing data, communicating business insights Tech Stack: Python data science stack (e.g., pandas, scikit-learn, pytorch, plotly, etc.) Engineering Tasks: Implement model training pipelines, create plots and visualizations to communicate insights, write re-usable modeling code Collaborative Aspect: Works closely with MLEs, other data scientists, product, customer success, QA MUST HAVE: A BA or greater in Data Science or Math or equivalent.
Use the capabilities of our AI Platform to deploy production solutions for our customers.
Work with customer data and own the development of an AI solution from ideation to production
Leverage integrations with big data frameworks (e.g. Databricks) as needed to develop solutions for customers. Primary Focus: Exploratory data analysis, model selection, feature engineering, hyperparameter tuning, setting up backtesting/evaluation frameworks, and some data engineering and SWE tasks Technical Skills: Foundational knowledge in data science/ML/CS Core Strengths: Choosing appropriate models, analyzing data, communicating business insights Tech Stack: Python data science stack (e.g., pandas, scikit-learn, pytorch, plotly, etc.) Engineering Tasks: Implement model training pipelines, create plots and visualizations to communicate insights, write re-usable modeling code Collaborative Aspect: Works closely with MLEs, other data scientists, product, customer success, QA MUST HAVE: A BA or greater in Data Science or Math or equivalent.
Skills
Scikit-learn
Databricks
Pandas
PyTorch
Python
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