Data Scientist, Mid

Booz Allen Hamilton•Coronado, CA

2d•$77,600 - $176,000

About The Position

Booz Allen is seeking a data scientist to analyze complex structured and unstructured datasets and turn them into useful information that supports client decisions and addresses challenges across the public and private sectors. The role involves working closely with clients and subject-matter experts to understand their questions, assess data, identify analytic opportunities, and deliver actionable decision support. The data scientist will develop algorithms, systems, predictive models, and data products, selecting appropriate tools and frameworks to produce objective insights from disparate data. The position may involve data pipelines, ETL processes, automated reporting, dashboards, self-service analytics, and operations-research methods, particularly in support of Naval Aviation, Marine Corps, readiness, maintenance, supply, force-generation, or enterprise analytics efforts. A Secret clearance is required. Compensation is projected at $77,600 to $176,000 annually, depending on factors including location, qualifications, experience, and organizational requirements.

Requirements

Experience with Python, SQL, and open-source machine-learning libraries.
Experience analyzing structured and unstructured data and developing predictive models, algorithms, and data products.
Experience applying regression, clustering, decision trees, and neural networks.
Knowledge of statistical analysis, model validation, experimental design, and A-B testing.
Ability to work with stakeholders and subject-matter experts to assess data quality, identify analytic opportunities, and deliver actionable decision support.
Secret clearance required.
Bachelor's degree and at least 3 years of experience in data science, data analytics, or statistical modeling; or an associate's degree and at least 7 years of such experience; or at least 9 years of such experience in lieu of a degree.

Nice To Haves

Experience supporting Naval Aviation, Marine Corps, readiness, maintenance, supply, force-generation, or enterprise analytics efforts.
Experience building data pipelines, ETL processes, or automated reporting using PySpark, Databricks, Python, SQL, or similar tools in cloud or distributed-computing environments.
Experience with Tableau, Qlik, Power BI, or front-end/UI development for dashboards and self-service analytics products.
Experience with discrete-event simulation, process modeling, optimization, or other operations-research methods.

Responsibilities

Analyze structured and unstructured data.
Develop predictive models, algorithms, and data products.
Apply statistical and machine-learning methods to derive insights from data.
Work with clients, stakeholders, and subject-matter experts to understand needs, assess data quality, and identify analytic opportunities.
Deliver actionable decision support to help clients make informed decisions.
Use suitable tools and frameworks to transform disparate data into objective answers.