Data Scientist

Judge Group, Inc.; Washington (District of Columbia); On-site; USD 69,000 - 74,000; Full time

Job summary

Judge Group, Inc. seeks a Data Scientist / Data Engineer to join our Washington, DC data team. This 100% onsite role blends data engineering with advanced analytics to build scalable pipelines and production-ready ML solutions.

The ideal candidate has 5+ years in DS/DE, strong Python and SQL, and hands-on experience with Spark/Databricks, Airflow, and cloud services (Azure/AWS). Public Trust clearance eligibility is required.

Qualifications

• Bachelor's degree in a quantitative field.
• 5+ years in a combined Data Scientist and Data Engineer role.
• Advanced proficiency in Python and strong SQL.
• Hands-on experience with Apache Spark and/or Databricks.
• Experience with Apache Airflow and ETL/ELT pipelines.
• Strong understanding of data warehousing, lakehouse concepts, and scalable data platforms.
• Experience building, training, and deploying ML models with cloud services.
• Knowledge of data quality, validation, and governance.
• Strong analytical and problem-solving skills.
• Excellent written and verbal communication.

Responsibilities

• Design, build, and maintain scalable data pipelines.
• Develop data models, warehouses, and lakehouse architectures.
• Create reliable ETL/ELT workflows and cloud-based pipelines.
• Ensure data quality through validation and governance processes.
• Optimize pipelines for performance and cost efficiency.
• Build, train, deploy, and monitor ML models.
• Develop solutions for prediction, classification, and analytics.
• Perform feature engineering, EDA, and statistical modeling.
• Implement MLOps including versioning, CI/CD, containerization, and monitoring.
• Partner with stakeholders to translate requirements into data solutions.
• Communicate findings to technical and non-technical audiences.
• Maintain documentation for pipelines and models.
• Mentor junior team members and promote best practices.
• Stay current with emerging technologies.

Skills

Python

SQL

Spark/Databricks

Airflow

ETL/ELT

Data Warehousing

Lakehouse

MLOps

Cloud (Azure/AWS)

Communication

Education

Bachelor's degree in Computer Science, Data Science, Engineering

Tools

Databricks

Azure

AWS

MLflow

TensorFlow

PyTorch

Job description

Location: Washington, DC Salary: $50.00 USD Hourly - $54.00 USD Hourly Description:

Data Scientist / Data Engineer

Location: Washington, DC (100% Onsite, 5 days/week)

Clearance: Public Trust (Must be eligible to obtain)

Pay Rate: $50 - $54/hr

Overview

We are seeking a versatile Data Scientist / Data Engineer to join a high-performing data team. This hybrid role combines advanced data engineering expertise with data science and machine learning capabilities. The ideal candidate will build and maintain scalable data infrastructure while developing predictive models, performing advanced analytics, and delivering actionable business insights.

This position requires a strong technical foundation, problem-solving skills, and the ability to collaborate effectively with cross-functional teams to turn raw data into production-ready solutions.

Key Responsibilities

Data Engineering

• Design, build, and maintain scalable data ingestion, processing, and transformation pipelines.
• Develop and optimize data models, data warehouses, and lakehouse architectures.
• Create reliable ETL/ELT workflows using modern data engineering tools and cloud services.
• Ensure data quality through validation, monitoring, and governance processes.
• Optimize data pipelines for scalability, performance, and cost efficiency.

Data Science & Machine Learning

• Build, train, deploy, and monitor machine learning and deep learning models.
• Develop solutions for prediction, classification, recommendation, and generative AI use cases.
• Perform feature engineering, exploratory data analysis (EDA), and statistical modeling.
• Conduct A/B testing, causal inference analysis, and predictive analytics.
• Implement MLOps best practices including model versioning, CI/CD pipelines, containerization, and production monitoring.

Collaboration & Leadership

• Partner with business stakeholders, analysts, and technical teams to translate requirements into solutions.
• Communicate complex analytical findings to both technical and non-technical audiences.
• Maintain clear documentation for data pipelines, models, and processes.
• Mentor junior team members and promote engineering and data science best practices.
• Stay current with emerging technologies and evaluate opportunities to enhance organizational capabilities.

Required Qualifications

• Bachelor's degree in Computer Science, Data Science, Engineering, or a related quantitative discipline.

• 5+ years of experience in a combined Data Scientist and Data Engineer role.

• Advanced proficiency in Python and strong SQL expertise.

• Hands-on experience with:

• Apache Spark and/or Databricks

• Apache Airflow

• ETL/ELT pipeline development

• Strong understanding of:

• Data warehousing concepts

• Lakehouse architectures

• Scalable data platform design

• Experience building, training, and deploying machine learning models.

• Experience working with Azure and AWS cloud-native data services.

• Knowledge of data quality standards, validation techniques, and governance frameworks.

• Strong analytical and problem-solving skills.

• Excellent written and verbal communication abilities.

Preferred Technical Stack

• Python (Pandas, Scikit-learn, TensorFlow, PyTorch)
• SQL
• Apache Spark
• Databricks
• MLflow
• Apache Airflow
• Azure
• AWS

Requirements

• Must be eligible to obtain and maintain a Public Trust clearance.
• Must be able to work onsite in Washington, DC, five days per week.

Medical, dental, and vision insurance are available to qualified candidates who meet eligibility requirements.