Senior Risk Analyst
AlphaSense
| Company | AlphaSense |
| Category | Finance |
| Location | Remote - India |
| Remote | Remote |
| Employment | Not stated |
| Level | Senior |
| Salary | Not stated by the employer |
| Posted | 13 Jul 2026 |
| Last verified | 3 Aug 2026 |
| Source | Employer career page (greenhouse) |
Description
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
AlphaSense is maturing its security risk management program and needs a Senior Risk Analyst to be a core builder and operator of that function. You will design, implement, and mature a risk framework that spans information security, AI, and operational risk—building toward a program that is quantitative-leaning, connected to live data sources, and actionable at every altitude from service owner to executive leadership. You will establish risk identification and scoring methodologies, own the enterprise risk register, and produce risk intelligence that drives real decisions. You will also support the TPRM function led by a dedicated TPRM lead, contributing to assessments and risk tracking as needed. You approach this with an AI-native mindset: using AI to monitor threat landscapes, analyze risk data, draft risk narratives, and surface emerging risks faster than a traditional manual program could. The goal is a risk function, not a risk register—one that measures outcomes and reduced exposure, not just activity.This is not a role for someone looking to maintain a program that already exists. AlphaSense is building a risk management discipline that we believe can serve as the blueprint for how AI-era companies measure, communicate, and act on risk. Risk management across the industry is still largely qualitative, reactive, and disconnected from the systems that generate real signal. We intend to change that—and we want someone on this team who shares that ambition and wants to be part of building the model that others will eventually follow.
Key Responsibilities
Risk Program Design & Maturation
Design and implement a structured risk management program, including risk taxonomy, scoring methodology, risk appetite statements, and escalation thresholds. Align the program with ISO 27005, NIST RMF, or ISO 31000 as appropriate. This is largely greenfield work—you will help define the architecture and continuously mature the discipline as the company scales.
Risk Register Ownership
Build and maintain the enterprise risk register as a living operational tool, not a compliance artifact. Lead periodic risk identification workshops with business, engineering, and legal stakeholders to surface new and evolving risks. Ensure every risk has a documented owner, risk rating, treatment decision, and remediation timeline—and that the register reflects current reality, not last quarter's snapshot.
AI-Augmented Risk Analysis
Leverage AI tools to monitor threat intelligence, identify patterns across risk data, accelerate risk narrative drafting, and keep the risk register current between formal review cycles. Build AI-assisted workflows that reduce manual risk review burden and surface emerging risks earlier. Apply judgment to validate AI
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