Product Manager Cyber Intel

Dataminr•NY - Remote, NY

5d•$124,000 - $182,500•Remote

About The Position

At Dataminr, you will lead the creation and development of our threat intelligence capabilities. This role is responsible for defining, executing and leading an effort to build and enhance the Dataminr threat intelligence collections and system. Collaborating with world class engineers and domain experts across the company, you will help to transform the threat intelligence at Dataminr. We are looking for a builder who excels in a dynamic, high-velocity environment—an individual equally skilled at guiding high-level product strategy and who has a deep understanding of threat intelligence. This US-based position offers the flexibility of working remotely or can be located in our New York or Virginia office. Working at Dataminr you’ll have the opportunity to tackle the most exciting trends in AI on a daily basis to power a revolutionary product that uncovers critical events around the world as they unfold. Regenerative AI: our AI technology, ReGenAI, is a new form of generative AI that automatically regenerates real-time Live Event Briefs as events unfold. Learn more here. Agentic AI: we recently launched our Agentic AI capability, what we’re calling our Intel Agents, that autonomously generates critical context for our clients on real-time events, threats, and risks allowing them to see the clearest, most accurate view of what’s happening on the ground. Learn more here Multimodal AI: our platform detects events from many different types of data (images, video, sensor data, audio, and text in over 150 languages). Learn more here.

Requirements

6+ years of experience in Product Management, with a track record of building cybersecurity products
Fluency in cyber security data and data modeling standards - comfort with STIX/TAXII-style ontologies, MITRE ATT&CK, and entity types like threat actor, intrusion set, malware, CVE, and IOC/IOAs.
Experience using or creating cybersecurity APIs. Experience using Postman, or other tools, to use APIs and analyze their output, and comfortable going deep enough with your team to unblock technical questions.
Experience with best practices in data visualizations to ensure the intelligence is communicated correctly to analysts using the platform.
Experience using Claude Cowork, Claude Code, and/or Google Gemini, and a point of view on how AI tooling changes how an integration team scopes and ships work.
A strategic thinker who can define a compelling product vision and multi-year roadmap.
Understanding of SaaS and on-prem platforms, is comfortable defining functional specifications for cybersecurity product integrations, and can credibly review and challenge your team's technical decisions.
An exceptional communicator and leader with excellent organizational, written, and oral skills who can coach, inspire and lead cross-functional teams, and present a roadmap and strategy to senior leadership and executives.
Analytical and action-oriented, you break down complex problems, use data to drive decisions across a portfolio of integrations, and are resilient, resourceful, and relentless in your pursuit of product excellence.

Responsibilities

Define a compelling product vision and multi-year roadmap for the Global Intel Graph portfolio, translating complex ideas into actionable plans and measurable business results, and setting priorities across multiple PMs and product lines.
Build solutions that scale. Lead the ideation, research, and validation of new data and product capabilities, creating new derivative intelligence.
Lead execution from concept to launch. Partner with a world-class engineering team to define requirements, manage the product data lifecycle, and deliver products that exceed customer expectations.
Manage a vast data warehouse with hundreds of billions of data points and indicators. Standardize complex cybersecurity entities across customer platforms to turn raw information into actionable insights, facilitating faster detection and response.
Ensure the quality and trustworthiness of AI features by leading the review and validation of subject matter expert (SME) data for document analysis and related AI/ML functions. Coordinate labeling, accuracy checks, and edge-case testing, and establish feedback loops to convert customer input into prioritized improvements. This will help maintain the accuracy and reliability of AI-generated intelligence.