Lead Data Scientist (Artificial Intelligence/Machine Learning)

Federal experience is not required. Experience may have been gained in the public sector, private sector or through Volunteer Service. One year of experience refers to full-time work; part-timework is considered on a prorated basis. To ensure full credit for your work experience, please indicate dates of employment by month/day/year, and indicate number of hours worked per week, on your resume. You must meet the following requirements by the closing date of this announcement. BASIC REQUIREMENTS All GRADES: EDUCATION: You must have a bachelor's or higher degree in mathematics, statistics, computer science, data science or other 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: A combination of education and experience that includes courses equivalent to a major field of study (30 semester hours) as shown in the paragraph above, plus additional education or appropriate experience. SPECIALIZED EXPERIENCE GRADE 14: In addition to the basic requirements, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-13 grade level in the Federal service. Specialized experience for this position includes: Designing, developing, integrating, testing, and supporting conversational AI solutions, virtual assistants, chatbots, digital messaging platforms, voice automation, interactive voice response (IVR) platforms, or generative AI-enabled customer engagement solutions in a production environment. Developing and optimizing natural language understanding (NLU), natural language processing (NLP), speech recognition, intent classification, entity recognition, conversational workflows, or automated self-service solutions supporting customer interactions across voice and digital channels. Designing, testing, implementing, and refining prompt engineering strategies, generative AI workflows, large language model (LLM) integrations, and AI-assisted customer engagement capabilities to improve automation, containment, customer experience, and operational outcomes. Integrating conversational AI, generative AI, voice, chat, messaging, or digital engagement platforms with enterprise applications, APIs, backend systems, authentication services, customer data platforms, or knowledge management solutions. Demonstrating subject matter expert (SME)-level proficiency in at least one modern programming language such as Java or Python, including development of backend services, automation, integrations, data processing pipelines, or conversational application logic. Analyzing customer interaction data, conversation transcripts, chat sessions, operational metrics, and user behavior to identify trends, improve AI performance, evaluate model effectiveness, and enhance customer experience outcomes. Developing, querying, and analyzing large datasets using cloud-based analytics platforms and data warehouses to support AI model evaluation, operational reporting, and business decision-making. Troubleshooting and resolving complex system integration, application reliability, authentication, speech processing, conversational AI, generative AI, digital engagement, or performance issues across interconnected platforms. Applying DevSecOps, CI/CD pipelines, automated testing, version control, and agile software development practices in enterprise environments. Collaborating with business stakeholders, architects, engineers, cybersecurity personnel, data scientists, and operations teams to translate business requirements into AI-enabled technical solutions. AND You must also meet the following requirement(s): PERFORMANCE RATING: Current federal employees must have at least a fully successful or equivalent performance rating to receive consideration. TIME AFTER COMPETITIVE APPOINTMENT (TACA): By the closing date (or if this is an open continuous announcement, by the cut-off date) specified in this job announcement, current civilian employees must have completed at least 90 days of federal civilian service since their latest non-temporary appointment from a competitive referral certificate, known as time after competitive appointment. For this requirement, a competitive appointment is one where you applied to and were appointed from an announcement open to "All US Citizens" TIME IN GRADE (TIG): Federal employees must meet time-in-grade requirements. For positions above the GS-05, applicants must meet applicable time-in-­grade requirements to be considered eligible. One year (52 weeks) at the next lower grade level is required to meet the time-in-grade requirements for the grade you are applying for. For positions at the GS-05, you cannot advance to the GS-05 if you have held a GS-02 in the past 52 weeks. There is no TIG restriction for GS-02, 03, or 04 positions. For more information on qualifications please refer to OPM's Qualifications Standards.

The following are the duties of this position at the full working level. Serves as a Senior Data Scientist by leading advanced analytics projects, defining objectives, coordinating deliverables, evaluating team performance, and resolving challenges to ensure project success. Manages day to-day team operations, and driven outcomes aligned with the organization's goals. Responsibilities include obtaining approvals on project documentation, conducting code and model reviews, and ensuring project delivery acceptance. Communicates findings effectively, providing insights and training on complex analytics solutions to business partners at all levels. Collaborates with senior leaders, technical teams, and non-technical staff to address policy interpretations and translate technical challenges into actionable solutions. Champions IT's digital transformation with a focus on customer-centric, data-driven initiatives, ensuring the analytics environment evolves to meet business needs. Leads efforts to certify datasets, optimize processes for data extraction, transformation, governance, and cataloguing, and accelerate time-to-insights for business decision-making. Applies advanced knowledge of computer science, mathematics, and statistical theories to construct new analytical processes, interpret models, and report quantitative trends and relationships. Leads digital data and analysis efforts to enhance customer strategies, support platform development, and improve user experiences throughout the customer lifecycle. Ensures reports, analyses, visualizations, and dashboards accurately reflect critical information for digital services. Collaborates closely with managers and executives to advance IT analytics roadmaps, delivering enhanced data capabilities that support strategic business objectives.