Data Scientist

Take your career to the next level with the USPTO's Office of Information Technology for Patents, Office of Patent Automation. This position provides scientific expertise and data-driven analysis to support the business metrics, strategic planning, and organizational decision-making. The incumbent assesses and helps implement automated systems, tools, products, and processes that support next-generation technology and improve cost-effectiveness, efficiency, and productivity within the USPTO.

You must meet the United States Office of Personnel Management's (OPM) qualification requirements (including specialized experience and/or educational requirements) for the advertised position. You must meet all eligibility and qualifications requirements by the closing date of the job announcement. OPM Qualifications Standards are available at Data Scientist Series 1560. Applicants must meet the basic occupational qualifications requirements for this position as follows: Degree: Mathematics, statistics, computer science, data science or field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position. OR Combination of education and experience: Courses equivalent to a major field of study (30 semester hours) as shown in paragraph A above, plus additional education or appropriate experience. In addition to meeting the basic occupational requirements stated above. Specialized Experience is experience that has equipped applicants with the particular knowledge, skills and abilities to successfully perform the duties of the position, and that is typically in or related to the position to be filled. To be creditable, you must possess one full year (52 weeks) of specialized experience equivalent to GS-13 in the Federal service. Specialized experience for this position includes: Performing a variety of duties involving statistical and mathematical analyses in support of the information technology (IT) needs of the business unit; AND Collecting, integrating, and analyzing large structured and unstructured data from various internal and external sources, such as automated systems and tools, internal IT systems, and public databases to propose operational improvements; AND Preparing reports using machine learning, programming, and data visualization skills to present organization findings to senior leadership and executives; AND Developing innovative tools and algorithms to streamline workflows, improve efficiencies, identify shortfalls and gaps, troubleshoot data issues, and propose ways to mitigate program risk. Experience refers to paid and unpaid experience, including volunteer work done through National Service programs (e.g., Peace Corps, AmeriCorps) and other organizations (e.g., professional; philanthropic; religious; spiritual; community, student, social). Volunteer work helps build critical competencies, knowledge, and skills and can provide valuable training and experience that translates directly to paid employment. You will receive credit for all qualifying experience, including volunteer experience.