Data Scientist - Remote USA

ICF•Reston, VA

1d•$81,499 - $138,549•Remote

About The Position

ICF is seeking a Junior Data Scientist to join their Health Engineering Systems (HES) team. This role will support data exploration, analysis, modeling, validation, and visualization using various tools including PostgreSQL, SQL, Python, Databricks, and AWS QuickSight within the DataConnect reporting environment. The position is ideal for an early-career professional who is curious, detail-oriented, eager to learn new technologies, and capable of communicating findings to diverse audiences.

Requirements

Bachelor's degree
2+ years of experience using Python for data analysis, data preparation, and statistical modeling
Candidate must be able to obtain and maintain a Public Trust clearance.
Candidate 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.

Nice To Haves

Bachelor's degree in data science, statistics, mathematics, computer science, engineering, economics, or a related quantitative field.
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.
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 common 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 the development, testing, and documentation of statistical analyses, machine-learning models, and analytical workflows.
Develop and support notebooks and repeatable analytical workflows in Databricks.
Create and maintain clear 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.
Other duties as assigned.