Junior Data Scientist

Key Responsibilities

• Collect, clean, validate, and analyze structured and semi-structured program data.
• Build SQL, Python, and R scripts to extract data, run calculations, automate recurring analysis, and reduce manual reporting effort.
• Develop and maintain Tableau dashboards, visual reports, charts, and performance summaries.
• Support data quality reviews by identifying anomalies, missing values, inconsistent records, and reporting defects.
• Affiliate with senior analysts with statistical modeling, machine learning, trend analysis, and performance measurement.
• Translate complex datasets into clear summaries for non-technical stakeholders.
• Document data sources, business rules, transformation logic, assumptions, and analytical methods.
• Support recurring weekly, monthly, quarterly, and ad hoc reporting requirements.
• Review model outputs and error patterns to recommend improvements to analytical workflows.
• Collaborate with senior data scientists, program analysts, project managers, and government stakeholders.

Required Qualifications

• Bachelor’s degree in Data Science, Statistics, Computer Science, Mathematics, Information Systems, Neuroscience, Public Health Analytics, or a related quantitative field.
• 1–3 years of data science, data analytics, research analytics, BI, or machine learning project experience.
• Hands-on Python experience using pandas, NumPy, scikit-learn, matplotlib, spaCy, Keras, or similar libraries.
• R experience using tidyverse, tidymodels, ggplot2, Shiny, or equivalent packages.
• SQL experience for querying, joining, filtering, and preparing datasets.
• Tableau, Power BI, R Shiny, or similar dashboard/data visualization experience.
• Experience with machine learning classification, NLP, model evaluation, or predictive analytics.
• Ability to inspect model errors, validate outputs, and communicate improvement opportunities.
• Strong Excel and Microsoft Office skills.
• Ability to explain technical findings to non-technical stakeholders.
• U.S. citizenship and ability to obtain required federal suitability/clearance.

Preferred Qualifications

• Active Secret clearance or prior federal suitability.
• Experience with federal, public sector, law enforcement, financial, healthcare, biomedical, or large statistical datasets.
• Experience supporting performance metrics, KPI reporting, operational reporting, or program evaluation.
• Experience building client-facing dashboards or interactive data applications.
• Experience with BERT, NLP, unstructured text, topic segmentation, or terminology data.
• Familiarity with data governance, data privacy, PII handling, CUI, or secure data environments.
• AWS, Git, Jupyter Notebook, or cloud analytics exposure.