Data Scientist - Remote USA

ICF•Reston, VA

14d•$81,499 - $138,549•Remote

About The Position

ICF is seeking an early-career Data Scientist to support its Health Engineering Systems team in turning data into actionable insights. The role involves data exploration, analysis, modeling, validation, and visualization using PostgreSQL, SQL, Python, Databricks, and the DataConnect reporting environment with AWS QuickSight. The position is remote, but all work must be performed in the United States, and the employee must reside in the United States. The candidate must be able to obtain and maintain a Public Trust clearance. The successful candidate will be curious, detail-oriented, comfortable learning new technologies, and able to communicate findings to technical and non-technical audiences. They will collaborate with data engineers, stakeholders, and senior team members; follow applicable data privacy, security, governance, and responsible-use standards; and participate in Agile planning, peer reviews, and ongoing learning.

Requirements

Bachelor's degree.
At least 2 years of experience using Python for data analysis, data preparation, and statistical modeling.
Ability to obtain and maintain a Public Trust clearance.
Must reside in the United States, be authorized to work in the United States, and have lived in the United States for three full years out of the last five years.
Academic, internship, project, or professional experience using Python for data analysis.
Foundational SQL skills, including joins, aggregations, filtering, and data validation.
Understanding of core statistics, data preparation, exploratory analysis, and model-evaluation concepts.
Ability to communicate analytical methods and findings clearly in writing and presentations.
Ability to work collaboratively, manage assigned tasks, and incorporate feedback.

Nice To Haves

Bachelor's degree in data science, statistics, mathematics, computer science, engineering, economics, or a related quantitative field.
Experience with PostgreSQL or another relational database platform.
Experience using Databricks, Spark, notebooks, or cloud-based analytics platforms.
Experience creating data visualizations or dashboards with AWS QuickSight or a comparable business-intelligence tool.
Experience with Python data-science libraries such as pandas, NumPy, scikit-learn, or PySpark.
Familiarity with TypeScript and its use in data applications, dashboards, services, or integrations.
Familiarity with Git, code reviews, unit testing, CI/CD, or Agile development practices.
Exposure to data governance, metadata, data quality, privacy, or responsible AI practices.
Experience working with health, public-sector, or other regulated data environments.

Responsibilities

Use SQL and Python to extract, clean, transform, and analyze structured data from PostgreSQL and other approved sources.
Perform exploratory data analysis to identify patterns, trends, anomalies, and data-quality issues.
Assist with developing, testing, and documenting statistical analyses, machine-learning models, and analytical workflows.
Develop and support notebooks and repeatable analytical workflows in Databricks.
Create and maintain visualizations, datasets, and reports for DataConnect using AWS QuickSight.
Validate analytical outputs and document assumptions, methods, limitations, and results.
Partner with data engineers to define data needs, resolve quality issues, and improve the usability of analytical datasets.
Translate business questions into measurable analyses with guidance from senior team members and stakeholders.
Write reusable, version-controlled code and basic unit tests for analytical functions and data transformations.
Present findings through concise written summaries, visualizations, and team demonstrations.
Follow established standards for data privacy, security, governance, and responsible use of data.
Participate in Agile planning, refinement, peer reviews, and continuous learning activities.
Perform other duties as assigned.