Data Scientist

Booz Allen Hamilton•Atlanta, GA

2d•$77,500 - $176,000•Hybrid

About The Position

As a Data Scientist at Booz Allen, you will analyze complex structured and unstructured data to help clients address challenges across private and public sectors. You will work with clients to understand their questions and needs, explore data-rich environments, develop algorithms and systems, and select tools and frameworks to transform disparate data into useful information that supports informed decisions. The role applies data science, machine learning, and artificial intelligence to real-world problems. This position is hybrid in Atlanta, Georgia, and requires the ability to obtain and maintain a Public Trust or Suitability/Fitness determination based on client requirements. Applicants selected will be subject to a government investigation and may need to meet U.S. government client eligibility requirements.

Requirements

3+ years of experience with data exploration, data cleaning, data analysis, data visualization, or data mining using programming languages such as Python, R, or SQL.
3+ years of experience designing, developing, and maintaining end-to-end production data pipelines.
Experience implementing data quality, observability, monitoring, data security, and enterprise data governance.
Experience collaborating with business stakeholders, gathering requirements, and delivering technical presentations to technical and non-technical audiences.
Experience analyzing structured and unstructured data sources using machine learning and natural language processing methods.
Ability to obtain and maintain a Public Trust or Suitability/Fitness determination based on client requirements.
Bachelor’s degree.

Nice To Haves

2+ years of experience with business analysis processes, including translating scientific or technical requirements into user stories, use cases, and platform features.
2+ years of experience with Microsoft Azure, including Azure Data Factory, Azure Functions, or Azure Storage, or with cloud platforms such as AWS or Google Cloud Platform (GCP).
Experience deploying and supporting applications in a cloud environment.
Knowledge of Agile development methodologies, DevOps, and DataOps practices.
Master’s degree.

Responsibilities

Explore, clean, analyze, visualize, and mine data using programming languages such as Python, R, or SQL.
Design, develop, and maintain end-to-end production data pipelines.
Implement data quality, observability, monitoring, data security, and enterprise data governance.
Collaborate with business stakeholders to gather requirements and deliver technical presentations to technical and non-technical audiences.
Analyze structured and unstructured data using machine learning and natural language processing methods.
Develop algorithms and systems and use appropriate tools and frameworks to turn disparate data into useful information for client decision-making.