Lead Data Scientist (Artificial Intelligence/Machine Learning)
What you'd do
WHAT IS INFORMATION TECHNOLOGY? A description of the business units can be found at: https://www.jobs.irs.gov/about/who/business-divisions Position(s) are to be filled in the following area(s): IT - Taxpayer Services and Online Accounts Consider each location carefully when applying. If you are selected for a location, that location will become your official post of duty. REVIEW THE ADDITIONAL INFORMATION BELOW FOR FURTHER DETAILS
Major duties
The following are the duties of this position at the full working level. If this vacancy includes more than one grade and you are selected at a lower grade level, you will have the opportunity to learn to perform these duties and receive training to help you grow in this position. 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. Participates in defining project objectives for advanced analytics, supervised and unsupervised machine learning (ML), and AI solutions. Collaborates with business units to gather requirements, establish metrics, and outline expected outcomes. Develops innovative approaches and methodologies, applying advanced operations research and data science techniques such as statistical analysis, forecasting, predictive modeling, prescriptive analysis, and optimization. Validates methodologies and outcomes to ensure accuracy and alignment with objectives. Identifies and implements methods, processes, algorithms, tools, and systems to extract insights from structured and unstructured data sets across the data science lifecycle. Responsible for developing algorithms and tools for data manipulation and processing and using data visualization techniques to clearly articulate findings for stakeholders.
What you need to qualify
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: 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 requirements: MINIMUM AGE REQUIREMENT: Minimum age for federal employment is 18 years old, or at least 16 years old and have: Graduated from high school or been awarded a certificate equivalent to graduating from high school; or Completed a formal vocational training program; or Received a statement from school authorities agreeing with your preference for employment rather than continuing your education. For more information on qualifications please refer to OPM's Qualifications Standards.
Before you apply
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