The Role
Kumo.ai is redefining enterprise AI with foundation models for relational data, enabling businesses to make more accurate decisions through intelligent predictions. Our mission is to build AI-powered solutions that help organizations predict, optimize, and act autonomously—transforming how data scientists and analysts work with structured data. Our breakthrough in Relational Deep Learning and Graph Transformers automate feature engineering, allowing users to build powerful ML models with just a few lines of Predictive Query. We're creating intuitive interfaces that connect complex AI backends with delightful user experiences, making sophisticated AI accessible to users across the enterprise.
The Role - We're seeking a Product Manager to drive the development and execution of a strategic roadmap of initiatives that allows us to scale the adoption and impact of our revolutionary AI-powered products. You'll collaborate with cross-functional teams to translate complex machine learning capabilities into valuable, intuitive solutions that solve real customer problems and deliver measurable business impact.
Outcomes for the first 12-18 months
- Partnering with the CEO, Head of Engineering, and Chief Scientist, drive the creation of a roadmap of strategic priorities that helps Kumo achieve its high level vision and strategy.
- Drive strategy and execution of several product initiatives that enable the closing of new enterprise contracts, increase customer satisfaction and decrease support contacts (E.g. model explainability features, cost estimation reporting, connectivity & integrations). Including being very hands on in developing technical specifications, not just program management.
- Drive continuous improvement to the UX implementing the right evaluation metrics, customer feedback loops and test plans.
- Implement a process to source product feedback from customers and internal partners and integrate it into roadmap prioritization. Effectively bring stakeholders along providing regular communications and check-points into prioritization decisions.
- Define a plan to identify, triage, prioritize and address technical and product debt in a systematic way (e.g. talking with sales teams, customers, user session research).
- Conduct open ended research (market, data analysis) to inform future direction of the product.
Competencies
- Ownership mindset & impact orientation - Identifies and owns dependencies to sequence complex workstreams and is relentless about shipping impactful work that drives results.
- Technically strong - Has a proven track record of specifying and driving execution of deeply technical products (e.g. APIs, infrastructure, production ML models).
- Domain expertise in ML/AI products - Has domain knowledge in Machine Learning and can build and ship ML products. Is excited to become an industry leader and internal ambassador.
- Strong product instincts - Combines analytical thinking with strong intuition and empathy for user needs to consistently predict what customers want and explain why.
- Strategic thinking & business acumen - Expresses good judgment in prioritizing work that drives business impact.
- Data driven and analytical - Uses data effectively to inform strategic decisions and to problem solve. Distills key insights from complex analysis.
- Excellent communicator - Articulates strategy crisply, uses compelling narrative to rally teams and stakeholders around ambitious goals. Translates complex technical products and decisions into simple, concise language.
- Raw intelligence - Able to synthesize information and derive first principles.
- Great collaborator - Builds strong relationships across functions (data, engineering, GTM, ops) and can effectively align disparate parts of an organization.
Key Responsibilities:
- Develop deep understanding of customer needs through market research, user interviews, and data analysis
- Define product requirements, prioritize features, and collaborate with engineering and design teams on implementation
- Create and manage product roadmaps that align with company strategy and goals
- Use data and metrics to measure product success and inform decision-making
- Collaborate with sales and marketing teams to develop go-to-market strategies and product positioning
- Serve as the voice of the customer, advocating for user needs throughout the product development process
- Balance technical feasibility with business objectives and user experience
- Communicate product vision effectively to both technical and non-technical stakeholders
Minimum qualification:
- BS (preferred MS, MBA) in Computer Science, Business, or related field, or equivalent experience
- 3+ years of experience in product management, preferably in enterprise software or data/analytics products
- Strong understanding of software development lifecycle and agile methodologies
- Experience working with technical teams and translating complex concepts for different audiences
- Data-driven approach to decision making with ability to define and track KPIs
- Excellent communication, presentation, and stakeholder management skills
- Basic understanding of machine learning concepts and data workflows
Preferred Qualifications
- 5+ years of relevant experience in product management
- Experience with AI/ML products or platforms
- Background in data science, analytics, or related technical field
- Experience building and launching SaaS products or working in Enterprise companies
- Demonstrated ability to drive product adoption and growth
- Experience with user research and usability testing methodologies
- Understanding of relational data, SQL, and data transformation concepts
- Strong project management skills with ability to balance competing priorities
- History of successfully bringing innovative products to market
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
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The Company
What We Do
Democratizing AI on the Modern Data Stack!
The team behind PyG (PyG.org) is working on a turn-key solution for AI over large scale data warehouses. We believe the future of ML is a seamless integration between modern cloud data warehouses and AI algorithms. Our ML infrastructure massively simplifies the training and deployment of ML models on complex data.
With over 40,000 monthly downloads and nearly 13,000 Github stars, PyG is the ultimate platform for training and development of Graph Neural Network (GNN) architectures. GNNs -- one of the hottest areas of machine learning now -- are a class of deep learning models that generalize Transformer and CNN architectures and enable us to apply the power of deep learning to complex data. GNNs are unique in a sense that they can be applied to data of different shapes and modalities.
