AlphaSense
Principal Product Manager, Financial Data
Remote - Canada · Principal
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About the role
- Candidates should have extensive experience managing complex data projects that span multiple teams paired with working knowledge of user workflows related to financial data (such as investor research, quantitative analysis, M&A, etc.).
Responsibilities
- Create the framework for a " zero-to-one" product lifecycle from initial data analysis through launch, including creating "user stories", product milestones and roadmap and supporting PMs to create detailed PRDs.
- Work alongside internal domain experts with deep capital markets / investment research experience to understand user pain points, validate product hypotheses, prompt innovation and inform prioritization.
- Partner with Directors to manage resourcing, reporting and milestone tracking across both major projects.
- Mentor and coach product managers in partnership with team leaders to elevate functional excellence, foster professional growth, and build high-performing product teams.
- Articulate core client problems and collaborate with engineers to validate potential solutions based on robust customer feedback, strategic objectives, market analysis, and technical feasibility.
- Demonstrate strong and persuasive communication skills, ensuring complex ideas are understood by cross-departmental partners, gaining alignment and buy-in to drive valuable impact.
- AlphaSense is the AI platform redefining market intelligence and workflow orchestration, trusted by thousands of leading organizations to drive faster, more confident decisions in business and finance.
- With AI solutions like Generative Search, Generative Grid, and Deep Research, AlphaSense delivers the clarity and depth professionals need to navigate complexity and obtain accurate, real-time information quickly.
- Analyze other relevant competing content sets in the market. and interact with customers to understand their workflows and pain points and gather and document actionable feedback.
Requirements
- 12+ years of product management experience, including several years the fintech, investment research, or financial services industry
- Proven track record of managing complex products with many moving parts.
- Experience with Notion and Linear
- Bachelor's degree in finance, accounting, or business, MBA or a CFA designation
Skills
- Strong communication skills and highly team-oriented
Compensation
- In order to be compliant with local legislation, as well as to provide greater transparency to candidates, we share salary ranges on all job postings regardless of desired hiring location.
Benefits
- You may also be offered a performance-based bonus, equity, and a generous benefits program.
- Remain vigilant of industry trends to deliver competitive intelligence to better evolve product and content vision.
Company info
- The Financial Data content organization is responsible for curating best-in-class structured data, both self-sourced and from third party content providers.
- The team was historically focused primarily on building a platform of 4,000+ fundamental financial models.
- 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 and enable users to unearth even more comprehensive insights from thousands of content sets.
- Within this new environment, the Global Research team is integrating our rich dataset into the platform alongside third party data to create a new final database that will offer our customers an unmatched level of accuracy, context, and flexibility to analyze and make investment decisions.
- We are seeking a Principal Product Manager to oversee and lead the integration of two major new product launches into the AlphaSense platform.
- We are committed to a work environment that supports, inspires, and respects all individuals.
This listing is sourced directly from AlphaSense's careers page and normalized into a canonical job model.