Type of Requisition:
RegularClearance Level Must Currently Possess:
NoneClearance Level Must Be Able to Obtain:
NonePublic Trust/Other Required:
MBI (T2)Job Family:
Data Science and Data EngineeringJob Qualifications:
Skills:
Agile Software Development, Data Validation, Measurement Reporting, Python (Programming Language), Statistical MethodsCertifications:
NoneExperience:
5 + years of related experienceUS Citizenship Required:
NoJob Description:
Own your opportunity to turn data into measurable outcomes for our customers’ most complex challenges. As a Data Scientist Senior at GDIT, you’ll power innovation to drive mission impact and grow your expertise to power your career forward.
The work you’ll do at GDIT will be impactful to the mission of the Centers for Medicare & Medicaid Services. You will play a crucial role in developing data-driven solutions to complex business challenges, using advanced tools and computational skills to interpret, connect, predict, and make discoveries in data.
MEANINGFUL WORK AND PERSONAL IMPACT:
- Contribute to completion of specific programs and projects.
- Utilize advanced tools (e.g., Python, PySpark, Databricks) and computational skills to interpret, connect, predict, and make discoveries in data.
- Collaborate with internal and external team members to achieve the mission.
- Evaluate the effectiveness and accuracy of new data sources and gathering techniques.
- Use predictive modeling to increase and optimize customer experience, efficiencies, process improvements, and other business outcomes.
- Optimize jobs performance and resource usage, identifying and addressing bottlenecks and inefficiencies in backend systems
- Write clean, well-structured, and maintainable code, adhering to established coding standards and best practices.
- Perform thorough code reviews, providing constructive feedback to peers and identifying potential risks or areas for improvement.
- Debug and resolve defects, proactively identifying and addressing potential issues before they impact users.
- Create and maintain comprehensive technical documentation.
- Actively participate in Agile ceremonies, such as stand-ups, sprint planning, and retrospectives, ensuring effective communication and collaboration across the team.
- Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
- May develop processes and machine learning based tools to monitor and analyze model performance and data accuracy.
- May coach and review the work of less experienced professionals.
- May serve as a team or task lead.
WHAT YOU’LL NEED TO SUCCEED:
- Education: Bachelor of Science
- Experience: 5+ years of related experience
- Python / Apache Spark, Databricks.
- Strong understanding of software design patterns, data structures, and algorithms.
- Experience with Agile development methodologies.
- Related experience in analytic programming, data extraction, querying databases/data warehouses and data analysis.
- SAS, R, AWS experience preferred.
GDIT IS YOUR PLACE:
- At GDIT, the mission is our purpose, and our people are at the center of everything we do.
- Growth: AI-powered career tool that identifies career steps and learning opportunities
- Support: An internal mobility team focused on helping you achieve your career goals
- Rewards: Comprehensive benefits and wellness packages, 401K with company match, and competitive pay and paid time off
- Community: Award-winning culture of innovation and a military-friendly workplace
OWN YOUR OPPORTUNITY
Explore a career in data science and engineering at GDIT and you’ll find endless opportunities to grow alongside colleagues who share your determination for solving complex data challenges.
The likely salary range for this position is $114,750 - $155,250. This is not, however, a guarantee of compensation or salary. Rather, salary will be set based on experience, geographic location and possibly contractual requirements and could fall outside of this range.Scheduled Weekly Hours:
40Travel Required:
NoneTelecommuting Options:
RemoteWork Location:
Any Location / RemoteAdditional Work Locations:
