Data Scientist

Everforth ECS is seeking a Data Scientist to work in our Arlington, VA office.

This candidate will serve as the primary point of contact to provide expert-level technical support and data-driven services across the CDM Data Services - BETSIE Program. Strong candidates will have a desire to drive strategic initiatives that take advantage of modern approaches to technology, data usage, and business delivery. Our customer's requirements are dynamic and complex. The ideal candidate must be a fast learner, and able to effectively engage resources and work across teams to decompose large, complex problems into workable solutions. An aptitude for learning, strategic planning, and the ability to effectively communicate at all levels of the organization are a must. Furthermore, the successful candidate will serve as the liaison for the customer's data improvement efforts, participating in regular meetings, representing the CDM Data Services - BETSIE program, and supporting the requirements gathering process.

Specific Duties Include:

• Ensuring technical and performance objectives related to data collection, processing, and analysis.
• Apply mathematical, statistical, and machine learning techniques to interpret and analyze structured and unstructured data produced by various applications.
• Showcase expertise in the machine learning lifecycle, including feature engineering, model training and validation, deployment, monitoring, and iterative improvement.
• Design, automate, and maintain data processing pipelines and workflows to facilitate efficient analysis and reporting, and the integration of AI/ML capabilities.
• Research, design, and implement algorithms to solve complex problems using programming languages such as Python or R, leveraging libraries like NumPy, Pandas, Scikit-learn, TensorFlow, or PyTorch.
• Handle high-volume and high-velocity data processing, indexing, and analysis requests using tools such as Apache Kafka, and NoSQL databases.
• Explore innovative solutions for data analysis and modeling to address complex challenges and optimize business performance.
• Utilize supervised and unsupervised machine learning techniques, including classification, forecasting, anomaly detection, and pattern recognition using methods such as decision trees, regressions, ensemble methods, and boosting algorithms.
• Follow programming best practices, emphasizing code reusability and implementing highly automated CI/CD pipelines for scalability.
• Communicate complex data findings and insights to non-technical audiences, translating results into actionable recommendations.
• Identify new and creative approaches to data efficiencies within the CDM Data Services - BETSIE program.