Emerging Markets Data Scientist: ML & Cloud Analytics Lead

US Commodity Futures Trading Commission; Washington (District of Columbia); On-site; USD 120,000 - 150,000; Full time

Job summary

US Commodity Futures Trading Commission seeks a candidate for a CT-14 level role focused on data science leadership. You will lead data science projects, provide technical guidance, and work with advanced statistical models, machine learning, and cloud-based analytics platforms.

You will mentor staff, present complex findings to senior management, and design and implement automated data science workflows and pipelines that scale across big data technologies.

Qualifications

• Degree in Mathematics, Statistics, Computer Science, Data Science or related field (bachelor level)
• OR combination of education and experience with 30 semester hours in a related major
• CT-14 requires at least one year of specialized experience equivalent to GS/CT-13

Responsibilities

• Experience leading data science projects and providing technical guidance.
• Experience in advanced statistical models, machine learning, big data technologies, and cloud-based analytics platforms.
• Experience mentoring staff and presenting complex findings to senior management.
• Experience designing and implementing automated data science workflows and pipelines.

Skills

Data science project leadership

Mentoring staff

Presenting complex findings

Statistical modeling

Education

Bachelor's degree in Mathematics, Statistics, Computer Science, Data Science or related field

30 semester hours combination of education/experience

Tools

Big Data technologies

Cloud-based analytics platforms

Automated data science workflows

Job description

US Commodity Futures Trading Commission seeks a candidate for a CT-14 level role focused on data science leadership. You will lead data science projects, provide technical guidance, and work with advanced statistical models, machine learning, and cloud-based analytics platforms.

You will mentor staff, present complex findings to senior management, and design and implement automated data science workflows and pipelines that scale across big data technologies.