Head of Assessment and Certification Content

About DataCamp Data and AI skills are critical for thriving today, and DataCamp is the platform that empowers everyone to learn them. We help individuals and Fortune 1000 companies close the data and AI skills gap through world-class learning, hands-on training, and a global community of expert instructors. In this role, you'll collaborate with instructors and teams across curriculum, engineering, product, and marketing to build and scale the assessments and certifications that prove those skills—helping millions worldwide validate what they've learned and signal it to employers. About the role This is an individual contributor role. You will own the design and production of DataCamp's assessment and certification content, working with subject-matter experts and building AI systems that generate, review, and continuously refresh high-quality, defensible questions at scale. Here's what your day-to-day will look like: Own the end-to-end lifecycle for assessment and certification content—from blueprint and item design through review, publication, and ongoing maintenance—and manage deadlines across it. Design psychometrically sound assessments: write and review items, define scoring and passing standards, and safeguard validity, reliability, and fairness. Build and operate AI workflows—prompting, pipelines, and evaluation—that draft, grade, and quality-check items, so content production scales without sacrificing rigor. Source and collaborate with subject-matter experts to keep certifications current with the fast-moving data and AI landscape. Map certifications to the real skills hiring managers screen for, so a DataCamp credential is a credible signal to employers. Benchmark against the wider certification landscape—competing programs, industry standards, and emerging role definitions—and set the strategy for where our certifications go next. Continuously assess certification performance using pass rates, item statistics, and learner and employer feedback to drive improvements. Qualifications: A technical background in a STEM field—such as Computer Science, Data Science, AI, Statistics, or Engineering—paired with experience evaluating technical competency (e.g., designing coding assessments, technical interviews, certification exams, or graded coursework), so you can judge whether an assessment item is accurate and genuinely tests skill. Demonstrated expertise in assessment design—item writing, scoring, standard-setting, and the validity, reliability, and fairness principles behind credible certification—with proven experience building or running technical assessments or certification programs. A clear grasp of the skills hiring managers actually screen for in data and AI roles, and how to translate them into what a certification measures. Strong experience with agentic AI systems such as Claude Code, Cursor, or Replit, and building AI automation systems. You can demonstrate you've increased your output 10x with AI. Graduate deg