Key Responsibilities:
Own product discovery and delivery for B2B SaaS Data & AI products (e.g. AI Pricing co-pilot data/analytics modules enterprise integrations).
Assist the founders to define product vision strategy and roadmap aligned with company objectives (profitability efficiency adoption retention).
Translate customer needs into clear PRDs user stories acceptance criteria and prioritised backlogsbalancing business value feasibility and time-to-market.
Partner with Engineering Data and ML teams to scope and deliver data-intensive and AI-driven features (pipelines model outputs monitoring governance explainability).
Drive product discovery: customer interviews problem framing workflow mapping competitive analysis and quantitative insights from product usage data.
Design end-to-end user experiences for enterprise workflows (admin permissions configuration integrations reporting) ensuring usability and trust in AI outputs.
Own success metrics and instrumentation: define KPIs/OKRs ensure events tracking analyse funnels and iterate based on adoption and impact.
Coordinate cross-functional execution: align stakeholders run sprint rituals when needed unblock delivery and maintain crisp communication across teams.
Work closely with Sales/Customer Success on enterprise deployments: onboarding enablement feature positioning feedback loops and roadmap communication.
Contribute to go-to-market readiness: packaging pricing inputs release notes demos and sales collateral for product launches and iterations.
Requirements:
Degree in Computer Science Engineering Business or related fields (or equivalent experience).
Proven track record delivering B2B SaaS products with measurable business impact (adoption revenue retention efficiency).
Strong product craftsmanship: PRDs prioritization frameworks roadmapping and stakeholder management in fast-moving environments.
Fluency with data/AI product fundamentals: metrics experimentation model lifecycle concepts data quality and AI/ML constraints.
Excellent analytical skills: ability to define and interpret KPIs structure ambiguous problems and make data-informed decisions.
Ability to communicate complex technical concepts clearly to non-technical stakeholdersand business context clearly to technical teams.
Hands-on understanding of modern data ecosystems and enterprise integrations (APIs ETL/ELT concepts data warehouses like Snowflake/Databricks cloud basics).
Experience in enterprise environments (security compliance governance permissions SLAs) is highly appreciated.
Joining our team youll have the chance to utilize cutting-edge technologies collaborate with top-tier professionals and contribute significantly to our data-driven decision-making processes. If youre passionate about machine learning and data engineering wed love to hear from you.
Full Visa Sponsorship and Healthcare.
Competitive package!