Junior Data Scientist / Performance Data Analyst I
Location: Washington, DC / Hybrid / Government Facility as Required
Clearance / Background: U.S. Citizen required; ability to obtain DOJ Public Trust and Secret clearance; active Secret preferred
Experience Level: 1–3 years
Role Summary
The Junior Data Scientist / Performance Data Analyst I supports a federal Management Information System program by helping collect, clean, validate, analyze, and visualize operational and performance data.
This role is ideal for an early-career data scientist with strong Python, R, SQL, Tableau, machine learning, NLP, and statistical analysis skills who is ready to progress from research, healthcare, or academic data work into federal mission analytics.
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.
- Assist 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.
Tools / Technologies
Python, R, SQL, Tableau, Excel, Jupyter Notebook, Git, AWS, pandas, NumPy, scikit-learn, spaCy, Keras, tidyverse, tidymodels, ggplot2, Shiny, NLP, BERT, dashboards, data visualization, statistical modeling.