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AlphaSense

Builds AI search tools for market research

Senior Risk Analyst

Security Governance, Risk & ComplianceConfirmed live in the last 24 hours
Full-timeRemote in IndiaNo salary listedRemote

About the Job

Requirements

  • At least 6 years of experience in GRC, information security, risk management, or IT audit, preferably in a SaaS or cloud-native environment.
  • Strong understanding of SOC 2, ISO 27001, NIST CSF 2.0, and CIS Controls, with working knowledge of ISO 42001 and NIST AI RMF.
  • Practical use of AI tools such as large language models, agents, and automation for substantive analysis, drafting, evidence gathering, and workflow automation, with judgment about where human review is needed.
  • Proficiency with GRC platforms for evidence management and control testing, such as Drata, Vanta, AuditBoard, ServiceNow GRC, or equivalent.
  • Familiarity with AWS, Azure, or Google Cloud Platform environments and security and compliance posture tooling such as cloud security posture management, security information and event management, and identity platforms.
  • Experience supporting external security or privacy audits, including evidence collection, control walkthroughs, and auditor interaction.
  • Ability to interpret technical controls and translate findings into compliance, risk, and policy documentation for engineers and non-technical stakeholders.
  • Working knowledge of risk registers, control libraries, and policy governance lifecycles.
  • Working knowledge of privacy and data protection requirements, including GDPR and CCPA/CPRA, and how they intersect with security controls, in partnership with Legal and Product teams.
  • Strong written communication, analytical thinking, and attention to detail, including producing audit responses, risk narratives, and control documentation under deadline.
  • At least 4 years of hands-on information security risk management experience or combined GRC/risk experience with responsibility for building or significantly maturing a risk register and scoring methodology.
  • Demonstrated use of AI or data tools to surface risk insights, analyze trends, draft risk narratives, or automate risk register workflows, validating AI output before it informs decisions.
  • Experience maturing an organization's risk program from qualitative to quantitative measurement, including scoring models, key risk indicator frameworks, and data-driven reporting that influenced leadership decisions.
  • Experience with data warehousing concepts, key risk indicator development and tracking, and risk reporting pipelines connecting live data sources to dashboards and executive reporting.
  • Proficiency with GRC platforms for risk tracking, control testing, and evidence management, such as Drata, Vanta, AuditBoard, ServiceNow GRC, or equivalent.
  • Strong analytical skills, including qualitative and quantitative risk scoring, heat maps, likelihood/impact matrices, and risk appetite articulation.
  • Experience producing executive-ready risk reports and translating technical findings into business-impact language for non-technical audiences.
  • Experience supporting third-party risk management assessments and contributing to vendor risk documentation in partnership with a dedicated third-party risk management function.

Responsibilities

  • Design and implement a structured risk management program, including risk taxonomy, scoring methodology, risk appetite statements, and escalation thresholds, aligning it with ISO 27005, NIST RMF, or ISO 31000 as appropriate.
  • Build and maintain the enterprise risk register as a living operational tool.
  • 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 keep the register reflective of current conditions.
  • Use 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; validate AI output before it informs risk decisions.
  • Support the third-party risk management function by contributing to vendor risk assessments, risk scoring, and finding documentation as needed.
  • Provide risk framework input to ensure third-party risks are consistently rated and tracked in alignment with the broader risk register.
  • Identify and assess AI-related risks, including data privacy, model bias, explainability, security misuse, agentic system behavior, and third-party AI dependencies.
  • Support compliance with AI governance frameworks, including ISO 42001, NIST AI RMF, and the EU AI Act; maintain current knowledge of the AI risk landscape and help address regulatory and operational risks from AI deployment.
  • Produce clear, executive-ready risk reports, dashboards, and periodic risk summaries.
  • Translate technical risk findings into business-impact language that supports decisions at the service owner, leadership, and board levels.
  • Provide cross-functional risk and control guidance on process improvements, new technology adoption, post-implementation reviews, and remediation activities.
  • Support stakeholders in interpreting risk requirements and embedding risk management practices into how they build and operate.

Desired Qualifications

  • Relevant certifications such as CISA, CRISC, CISM, CISSP, CCSK, or ISO 27001 Lead Auditor/Implementer.
  • Experience with AI governance frameworks, including ISO 42001, NIST AI RMF, the EU AI Act, or OECD AI Principles.
  • Exposure to SOX ITGC cycles, including managing evidence, walkthroughs, and findings with external auditors.
  • Privacy program crossover experience, including data mapping, DPIAs, and GDPR/CCPA operational compliance.
  • Scripting or automation experience with Python, JavaScript, or low-code tools applied to GRC or compliance workflows.
  • Quantitative risk experience using FAIR-style decomposition, Monte Carlo simulation, or loss exceedance analysis in real risk decisions.
  • Experience with AI risk domains such as model risk, algorithmic bias, AI system failure modes, and agentic system risks, and governance frameworks including NIST AI RMF or ISO 42001.
  • Familiarity with risk aggregation and business intelligence tools such as Tableau, Looker, or Power BI for risk dashboarding and executive reporting.
  • Background in financial services regulatory risk environments, such as SOX, FFIEC, or equivalent.

About the Company

AlphaSense

Builds AI search tools for market research

AlphaSense builds market intelligence software for investment professionals and corporate teams researching companies, competitors, and business trends. Its platform brings company filings, earnings calls, industry news, and expert interviews into a searchable library, so analysts work across sources rather than opening each document separately. AI tools interpret research questions, summarize findings, and link answers to the underlying material for review. Organizations also connect their internal research to the platform and pay subscription fees for access to its software and content. AlphaSense launched in 2011 and is headquartered in New York City.

Company size
1,001-5,000
Company stage
Late Stage VC
Total funding
$1.8B
Headquarters
New York City, New York
Founded
2011

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