Quick Overview
Job 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
- AWSRequirements
- Must be a U.S. Citizen.
- 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.
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