Compliance Analyst - AI Governance

About AlphaSense: The world’s most sophisticated companies rely on AlphaSense to remove uncertainty from decision-making. With market intelligence and search built on proven AI, AlphaSense delivers insights that matter from content you can trust. Our universe of public and private content includes equity research, company filings, event transcripts, expert calls, news, trade journals, and clients’ own research content. The acquisition of Tegus by AlphaSense in 2024 advances our shared mission to empower professionals to make smarter decisions through AI-driven market intelligence. Together, AlphaSense and Tegus will accelerate growth, innovation, and content expansion, with complementary product and content capabilities that enable users to unearth even more comprehensive insights from thousands of content sets. Our platform is trusted by over 6,000 enterprise customers, including a majority of the S&P 500. Founded in 2011, AlphaSense is headquartered in New York City with more than 2,000 employees across the globe and offices in the U.S., U.K., Finland, India, Singapore, Canada, and Ireland. Come join us! About the Role: The AI Governance Analyst is central to building and operating AlphaSense’s AI governance program, helping ensure that the way we deploy, build, and procure AI systems is well-governed, well-documented, and defensible to regulators, auditors, and enterprise clients. Sitting within the Strategic Risk team, this role owns the day-to-day execution of AI risk assessments — intake, classification, evaluation, and documentation — that keep the program running at scale. As AlphaSense matures its governance infrastructure, including the rollout of a dedicated GRC platform to automate assessment workflows, this role acts as the operational backbone of the program: turning frameworks such as the EU AI Act, NIST AI RMF, and ISO/IEC 42001 into repeatable, auditable processes that grow with the business. This is a risk and governance role — not a hands-on AI engineering role — well-suited to someone who understands how AI systems create risk and knows how to manage it. What You’ll Do: • Complete AI risk assessments using established templates and criteria — gathering details on AI use cases, working through classification and control questions, and preparing draft assessments for senior review. • Maintain the accuracy of the AI system inventory by adding and updating records of AI/ML systems, vendors, and use cases. • Leverage the AI governance platform to enter assessment data, follow set workflows, and organize supporting evidence and documentation. • Gather the information and evidence needed to map use cases against frameworks such as the EU AI Act, NIST AI RMF, and ISO/IEC 42001, with guidance on interpretation from senior team members. • Coordinate with engineering, product, security, legal and privacy, and procurement contacts to collect the details needed for assessments, and flag open questions for review. • Assist with third-party and vendor AI risk reviews by collecting vendor documentation and completing initial reviews for senior validation. • Draft clear, well-organized summaries and notes from completed assessments, and flag higher-risk or unclear items to senior reviewers. • Track the status of assessments and follow-ups, keeping records and trackers up to date so nothing slips through. Who You Are: • IAPP AIGP certified with a strong knowledge of the AI governance landscape and the major frameworks shaping it. • 2–4 years of experience in risk management, GRC, compliance, audit, or data privacy, with exposure to AI governance, technology risk, or third-party risk. • Familiar with the EU AI Act, NIST AI RMF, ISO/IEC 42001, and ISO/IEC 27001, and able to apply their requirements to real use cases rather than just cite them. • Comfortable working with GRC or governance tooling — configuring workflows, managing inventories, and generating reporting — and quick to learn new platforms. • AI-literate without being a developer: able to understand at a conceptual level how AI and ML systems work, the risks they introduce (bias, hallucination, data leakage, model drift, and similar), and how to translate that into governance language. • Highly organized and detail-oriented, capable of managing a high volume of assessments, inventory records, and deadlines at once without sacrificing quality. • A strong written and verbal communicator who can turn technical and regulatory complexity into clear assessments, summaries, and stakeholder-ready documentation in English. • A collaborative, self-directed partner who is comfortable with ambiguity and evolving priorities in a function that is being built from the ground up. • Organized, reliable, and able to manage multiple requests, track deadlines, and stay composed while handling a steady volume of work. 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