Data Scientist

UNAVAILABLE; McLean (VA); On-site; USD 120,000 - 180,000; Full time

Job summary

Unknown is seeking a Data Scientist to design, build, and deliver predictive analytics, ML models, and data-driven insights. You will work across engineering, data, and product teams to support mission and business outcomes and contribute to the full model lifecycle from data exploration to deployment.

Qualifications include a Master’s or Bachelor's in a relevant field, 6+ years of experience, strong Python and libraries, experience with PyTorch/TensorFlow/XGBoost, SQL, and cloud data platforms

Qualifications

• Bachelor’s or Master’s degree in a relevant field.
• 6+ years of experience building and evaluating ML models or performing advanced analytics.
• Proficiency in Python and core data science libraries (Pandas, NumPy, scikit-learn, Matplotlib/Seaborn).
• Hands-on experience with ML frameworks such as PyTorch, TensorFlow, XGBoost.

Responsibilities

• Conduct exploratory data analysis (EDA) to uncover trends and data quality issues.
• Develop ML models using frameworks such as scikit-learn, XGBoost, PyTorch, TensorFlow.

Skills

Python

Pandas

NumPy

scikit-learn

Matplotlib/Seaborn

PyTorch

TensorFlow

XGBoost

SQL

AWS

Azure

GCP

Databricks

Tableau

Power BI

EDA

Experiment design

Communication

Education

Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, Analytics, Engineering, Economics

Tools

Tableau

Power BI

AWS

Azure

GCP

Databricks

Job description

Overview

We are seeking aData Scientistto design, build, and deliver predictive analytics, machine learning models, and data-driven insights that support mission and business outcomes. This role requires strong analytical and modeling skills, hands-on experience with ML frameworks, and the ability to collaborate across engineering, data, and product teams. The Data Scientist will contribute to the full lifecycle of model development,from data exploration and feature engineering to model training, evaluation, and deployment,while supporting the articulation of insights and recommendations to technical and non-technical stakeholders.

Responsibilities

• Conduct exploratory data analysis (EDA) to uncover trends,identifydata quality issues, anddeterminemodeling opportunities.

• Develop machine learning models using frameworks such as scikit-learn,XGBoost,PyTorch, TensorFlow, or similar libraries.

• Perform feature engineering, dataset preparation, and model optimization to improve predictive accuracy and operational performance.

• Evaluate models usingappropriate statisticalmethods and performance metrics, documentingfindingsand informing iterative improvements.

• Work with Data Engineers to understand and enhance data pipelines, ensuring model-ready datasets areaccurate, complete, and consistent.

• Collaborate with AI Developers andLLMOps/MLOpsEngineers to integrate ML models into production environments or decision-support applications.

• Build visualizations, dashboards, data stories, and executive-friendly summaries to communicate insights clearly to stakeholders.

• Support human-centered design processes by translating user needs into modeling requirements and refining model outputs based on feedback.

• Contribute to reproducibility and auditability bymaintainingwell-organized code, notebooks, documentation, and experimenthistories.

• Stay current with modern data science methodologies, ML techniques, data processing tools, and cloud-enabled analytics workflows.

• You will contribute to the growth of our AI & Data Exploitation Practice!

Qualifications

• Ability to hold aposition of public trustwith the U.S. government.

• Bachelor’s orMaster’s degree inData Science, Computer Science, Statistics, Mathematics, Analytics, Engineering, Economics, ora related field.

• 6+ yearsof experience building and evaluating machine learning models or performing advanced analytics.

• ProficiencyinPythonand core data science libraries (Pandas, NumPy, scikit-learn, Matplotlib/Seaborn).

• Hands-on experience with at least one modern ML framework (e.g.,PyTorch, TensorFlow,XGBoost).

• Experience writing efficient SQL queries and working with structured or semi-structured data in cloud or database environments.

• Familiarity with cloud data and ML platforms such as AWS, Azure, GCP, or Databricks.

• Strong understanding of statistics, probability, experimental design, and model validation techniques.

• Ability to communicate technical concepts clearly to stakeholders and collaborate across multidisciplinary teams.

• Experience with dashboarding tools (Tableau, Power BI) or Python visualization libraries is a plus.

• Curiosity and adaptability, with a drive to stay current in rapidly evolving data and ML practices.

• Relevant certifications (helpful but notrequired):Databricks Data Scientist Associate, AWS ML Specialty, Azure Data Scientist Associate, Google Professional Data Engineer.