Data Scientist, Big Data/Cloud | TS Clearance Eligible

ecsfederal; Virginia (MN); On-site; USD 155,000 - 180,000; Full time

Job summary

ECS Federal seeks a Data Scientist to work on-site at the Springfield, VA customer’s office, supporting Big Data/Cloud solutions and agile projects. The candidate will manage, manipulate, and parse data for various applications within a multidisciplinary team, under deadlines critical to national security.

The role requires experience with data extraction/manipulation using Python, Linux scripting, and building data services and pipelines in an Agile/Scrum environment.

Qualifications

• Bachelor's degree in a related field required.
• 5+ years of experience in Data Science or Computer Science or Engineering.
• Proficient parsing data in formats for ML applications.
• Experience with Python for data extraction and manipulation.
• Proficient with Linux shell scripting.

Responsibilities

• Extract, transform and standardize data from multiple sources for ingest into consolidated environments.
• Support continuous data ingest automation.
• Develop and integrate applications for analytic workflows.
• Design and develop data services/pipelines as part of an Agile/Scrum team.
• Collaborate with program management and engineers to document complex requirements.
• Perform multiple tasks under changing deadlines and priorities.
• Promote customer service, innovation, collaboration, and teamwork.

Skills

Data Science

Python

Linux scripting

Data parsing

ML pipelines

Agile/Scrum

Education

Bachelor's Degree

Tools

Linux

SQL

ETL tools

Big Data

Job description

ECS Federal seeks a Data Scientist to work on-site at the Springfield, VA customer’s office, supporting Big Data/Cloud solutions and agile projects. The candidate will manage, manipulate, and parse data for various applications within a multidisciplinary team, under deadlines critical to national security.

The role requires experience with data extraction/manipulation using Python, Linux scripting, and building data services and pipelines in an Agile/Scrum environment.