Senior Product Manager

The Product Manager is responsible for the product planning and execution throughout the Product Lifecycle, including gathering and prioritizing product and customer requirements, defining the product vision, and ensuring revenue and customer satisfaction goals are met. The Product Manager’s job also includes ensuring that the product supports the company’s overall strategy and goals.

• ML literacy
• Stakeholder communication
• Designing for expert users without alienating new ones
• Clear documentation and onboarding flows
• Understanding user workflows—not just APIs

• Experimentation and metrics fluency
• Responsible AI leadership
• Platform UX thinking

• Align business leaders, engineers, data scientists, legal/compliance, and ops
• Translate technical constraints into business‑relevant language
• Manage expectations around ML uncertainty and iteration

• Data lineage and observability
• Metadata, schemas, and versioning

• APIs, SDKs, and self‑service capabilities
• Performance, scalability, and cost tradeoffs

• Supervised vs. unsupervised learning
• Features, labels, and training data

• ML outputs are probabilistic
  , not deterministic
• Improving models often requires better data
  , not better algorithms
• ML development is experimental and iterative

• Model monitoring and retraining
• Versioning of models and data
• Rollbacks and experimentation (A/B tests, canary releases)

• Business metrics (revenue, conversion, cost savings)
• Data metrics (coverage, freshness, null rates)
• Designing experiments when outcomes aren’t binary
• Interpreting noisy or delayed signals
• Knowing when not to trust metrics blindly