Remote Data Scientist — AI, ML & Data for Impact

Bah; Washington; On-site; USD 78,000 - 176,000; Full time

Job summary

Booz Allen is seeking a Data Scientist to unlock insights from large data sets across IoT and AI domains. You will partner with clients to frame questions, then build models and visualizations that translate data into actionable answers for complex challenges.

You'll lead teams, apply NLP and machine learning methods, and ensure solutions scale in real-world environments while maintaining a strong focus on data quality and impact.

Qualifications

• 5+ years of data exploration, data cleaning, data analysis, data visualization, or data mining.
• 5+ years of experience with statistical and general‑purpose programming languages for data analysis.
• 5+ years of experience analyzing structured and unstructured data sources.
• Experience developing predictive data models, quantitative analyses, and visualization of targeted data sources.
• Experience leading the development of solutions to complex programs.
• Experience with natural language processing, text mining, or machine learning techniques.
• Ability to obtain and maintain a Public Trust or Suitability/Fitness determination based on client requirements.
• Bachelor’s degree

Responsibilities

• Lead development of algorithms and data solutions.
• Collaborate with clients to define questions and needs.
• Deliver data-driven insights and visualizations.
• Guide teammates and manage projects.

Skills

Data exploration

Data cleaning

Data analysis

Data visualization

Data mining

Education

Bachelor’s degree

Tools

Python

R

SQL

NoSQL

Job description

Booz Allen is seeking a Data Scientist to unlock insights from large data sets across IoT and AI domains. You will partner with clients to frame questions, then build models and visualizations that translate data into actionable answers for complex challenges.

You'll lead teams, apply NLP and machine learning methods, and ensure solutions scale in real-world environments while maintaining a strong focus on data quality and impact.