Data Analytics Specialist

Data Analytics Specialist

• 401(k)
• Dental insurance
• Health insurance
• Paid time off
• Tuition assistance
• Vision insurance

As a member of the Science and Research Team, you are responsible for leading USADA’s data analytics and reporting strategy and leading cross‑functional projects to strengthen anti‑doping deterrence and detection efforts. You act as a vital bridge between Science, IT and business operations, translating data through analytics and visualizations into creative and well‑designed real‑time solutions to drive USADA’s anti‑doping program. You represent USADA in global collaborations, foster innovation and creativity, and promote a data‑driven culture.

You actively contribute to the daily operation, development and maintenance of the resources critical to the Science & Research team, and lead innovative projects with external collaborators.

• Lead USADA’s data analytics and reporting strategy, delivering data‑driven solutions, intuitive reporting, and cross‑functional project management to support deterrence and detection, target testing and real‑time risk analysis strategies.
• Bridge IT and business needs by developing robust, compliant infrastructure, tailored digital solutions, and optimized data flows to support analytical and operational priorities.
• Direct product development, data pipelines, models, automated processes, and ensure maintenance of analytics resources.
• Apply advanced statistical techniques such as data mining, predictive modeling, machine learning, and AI to identify patterns, trends, and correlations in large, structured datasets gathered through athlete performance, biological data or other relevant metrics, generating actionable outcomes for anti‑doping strategies.
• Design, build, and oversee dashboards, reports, validation of data, and visualization tools to provide timely insights and empower decision‑making.
• Identify, evaluate and maintain the most robust and informative data sets (performance metrics, etc…) to inform meaningful risk assessment strategies.
• Conduct substance reviews, open‑source research, scientific literature reviews, and prepare technical reports, presentations, and briefs for internal and external stakeholders.
• Support scientific and testing strategies by maintaining sample retention/reanalysis programs, compiling reference material, and contributing to risk assessment strategies.
• Represent USADA in global collaborations, foster relationships, and promote a data‑driven culture through innovation and effective communication.
• Create reports and track testing progress of specific Team USA athletes leading into major events (e.g. Olympics / Paralympics) to inform Testing and Science decisions in critical pre‑games periods.
• Maintain the Declaration Review Tool to assist the Drug Reference team with declaration reviews.

• Collaborate with the Science Team and other anti‑doping experts to create and evaluate individual athlete test profiles, including researching open‑source internet databases and other sources to support individual and sport‑based evaluations.
• Work with project personnel, to include vendors, partners, and clients to ensure project deadlines are met.
• Collaborate with colleagues in USADA to identify business requirements and how these can be included within a subsequent Data Analytics Strategy.
• With support of the Director of Science, lead projects with outside collaborators to advance USADA’s athlete and sport risk assessment strategies and cooperate with other anti‑doping organizations to learn and share data analytics expertise.
• Attend and present at scientific meetings and conferences as necessary to remain knowledgeable about the latest sport performance analytics, data analytics trends, and statistical and programming methodology and software tools.
• Represent USADA and contribute to online discussions and working groups of international data analytics working groups within the anti‑doping community.

• Collaborate closely with the Principal Data Engineer for production analytics: data pipelines, model services, feature stores, and versioned datasets.…