Key Responsibilities
Plan and perform the determination of appropriate methods to creatively explore, mine, analyze, and manipulate extremely massive datasets.
Develop and analyze modeling and measuring techniques using mathematics, machine learning, statistical methods, and engineering approaches to discover multiple solutions to complex problems.
Design and implement advanced predictive, prescriptive, and descriptive models to support mission-critical decision-making.
Create user-friendly reports and dashboards using various databases, analyses, programs, and scripts.
Collaborate with data engineers to ensure connectivity and integration between various databases, programs, and systems.
Work closely with stakeholders to understand analytical problems and develop tailored solutions.
Communicate results and insights in a clear, concise, and broadly understandable manner to technical and non-technical audiences.
Stay current with emerging trends and technologies in data science, machine learning, and artificial intelligence.
Provide technical leadership and mentorship to junior data scientists and analysts.
What you need to have
Security Clearance: Active SECRET Security Clearance with eligibility for TS/SCI.
Education & Experience (Gate Requirements – No Substitution)
Bachelor’s degree in Data Science, Computer Science, Applied Mathematics, Statistics, or related field with 8–10 years of experience; OR
Master’s degree with 6–8 years of experience; OR
PhD with 3–5 years of experience.
Strong experience in designing and implementing machine learning models and statistical techniques.
Expertise in Python, R, or equivalent programming languages for data analysis and modeling.
Proficiency in SQL and working with relational/non-relational databases.
Experience with distributed computing frameworks such as Spark or Databricks.
Familiarity with cloud platforms such as AWS (SageMaker, Redshift, Glue) or Azure equivalents.
Strong knowledge of data visualization tools such as Tableau, Power BI, or equivalent.
Experience with version control practices (Git).
Ability to work with structured, semi-structured, and unstructured data sources.
What we'd like you to have
Experience supporting DoW enterprise data platforms.
Familiarity with RMF, NIST 800-53, and DoD IL-level cloud environments.
Experience with natural language processing (NLP) and computer vision techniques.
Knowledge of metadata management, data cataloging, and governance tools.
Experience operating within Agile or DevSecOps environments in government programs.
Pay transparency
Please note the targeted compensation range is provided as an estimate, and any actual compensation offer may vary depending on the needs of the company, or an applicant's skillset, competencies, experience, education, certifications, location, or other factors. The estimated range does not include the value of any benefits offered.
About BigBear.ai
BigBear.ai is a leading provider of AI-powered decision intelligence solutions for national security, supply chain management, and digital identity. Customers and partners rely on Bigbear.ai’s predictive analytics capabilities in highly complex, distributed, mission-based operating environments. Headquartered in McLean, Virginia, BigBear.ai is a public company traded on the NYSE under the symbol BBAI. For more information, visit https://bigbear.ai/ and follow BigBear.ai on LinkedIn: @BigBear.ai and X: @BigBearai.
BigBear.ai is an Equal opportunity employer all protected groups, including protected veterans and individuals with disabilities.
As a Lead Data Scientist at BigBear.AI, you will lead the design, development, and implementation of advanced analytical models and techniques to solve complex problems using massive datasets. You will creatively explore, mine, analyze, and manipulate data to uncover actionable insights, develop innovative solutions, and enable decision-making across mission-critical DoW operations.
You will collaborate with stakeholders, data engineers, and analysts to ensure seamless integration of analytical solutions into operational workflows. You will also communicate results in a manner that is broadly understandable, enabling stakeholders to act on insights effectively.
Key Responsibilities
Plan and perform the determination of appropriate methods to creatively explore, mine, analyze, and manipulate extremely massive datasets.
Develop and analyze modeling and measuring techniques using mathematics, machine learning, statistical methods, and engineering approaches to discover multiple solutions to complex problems.
Design and implement advanced predictive, prescriptive, and descriptive models to support mission-critical decision-making.
Create user-friendly reports and dashboards using various databases, analyses, programs, and scripts.
Collaborate with data engineers to ensure connectivity and integration between various databases, programs, and systems.
Work closely with stakeholders to understand analytical problems and develop tailored solutions.
Communicate results and insights in a clear, concise, and broadly understandable manner to technical and non-technical audiences.
Stay current with emerging trends and technologies in data science, machine learning, and artificial intelligence.
Provide technical leadership and mentorship to junior data scientists and analysts.
Security Clearance: Active SECRET Security Clearance with eligibility for TS/SCI.
Education & Experience (Gate Requirements – No Substitution)
Bachelor’s degree in Data Science, Computer Science, Applied Mathematics, Statistics, or related field with 8–10 years of experience; OR
Master’s degree with 6–8 years of experience; OR
PhD with 3–5 years of experience.
Strong experience in designing and implementing machine learning models and statistical techniques.
Expertise in Python, R, or equivalent programming languages for data analysis and modeling.
Proficiency in SQL and working with relational/non-relational databases.
Experience with distributed computing frameworks such as Spark or Databricks.
Familiarity with cloud platforms such as AWS (SageMaker, Redshift, Glue) or Azure equivalents.
Strong knowledge of data visualization tools such as Tableau, Power BI, or equivalent.
Experience with version control practices (Git).
Ability to work with structured, semi-structured, and unstructured data sources.
