Jobs at Fetcherr

Own and lead Fetcherr’s product function, including strategy, roadmap, lifecycle execution, and product team growth. Manage and mentor Product Managers, collaborate with Engineering, Data, and Design, and engage enterprise airline customers on requirements and roadmap direction. Partner with Sales and Customer Success to support onboarding, renewals, and expansion. Translate complex AI capabilities into user-friendly products and measurable commercial value while driving execution, prioritization, and accountability.

Architect and build a Kubernetes-native self-service platform on GCP: create controllers/operators, enforce everything-as-code (Terraform/Helm/GitOps), own production reliability with observability, SLOs and alerting, and enable secure, automated developer workflows.

Build and maintain Tableau reports and dashboards, administer Tableau Server, and translate complex datasets into clear insights for non-technical stakeholders. Work with SQL and ETL pipelines to integrate and optimize large-scale data, troubleshoot performance, and support analytics team deliverables. Communicate findings, collaborate with peers, and continuously learn.

Designs and operationalizes causal-uplift measurement frameworks for pricing models, leads data discovery, and conducts research on uplift measurement and A/B testing. Translates multidimensional data and airline business logic into actionable insights, models, and technical pipelines. Assesses ML system performance from a business perspective and communicates findings to technical, non-technical, and executive stakeholders while collaborating with revenue managers, analysts, and engineers.

Manage strategic client relationships across multiple industries, serving as the primary account contact and aligning Fetcherr’s AI products with customer objectives. Drive client initiatives, stakeholder coordination, product adoption, cross-sell opportunities, renewals, commercial discussions, and issue resolution. Analyze performance metrics, provide strategic recommendations, and represent client needs internally. Frequent travel to Genoa, Italy, approximately twice monthly, is required.

Lead strategic client relationships for enterprise accounts, drive product adoption and commercial outcomes, coordinate cross-functional teams for delivery, monitor performance metrics, support renewals and upsell, and represent client needs to influence product and service improvements. Travel for client meetings and events as needed.

Build and administer Tableau dashboards and reports, transform large datasets into actionable insights, optimize queries and ETL processes, collaborate with stakeholders, and support Tableau Server administration and performance monitoring.

Build and maintain scalable ML models and data pipelines for training and inference. Ensure data accuracy and efficiency across structured and unstructured sources, using orchestration, containerization, and distributed systems to support data science workflows.

Design and operationalize causal-uplift measurement frameworks, lead data discovery, research novel uplift/A-B testing approaches, translate multidimensional pricing data into business insights, and collaborate with revenue managers, analysts, and engineers to encode airline business logic into modeling pipelines.

Build and maintain models and data pipelines for training and inference. Ensure data accuracy, consistency, and scalability across structured and unstructured sources. Implement pipeline orchestration, containerized deployments, and distributed computing to support data science workflows and production ML systems.

Design and operationalize causal uplift measurement frameworks, lead data discovery, conduct research and experiments for uplift/A-B testing, translate complex data into actionable pricing insights, assess ML system impact in business contexts, and collaborate with revenue managers, analysts, and engineers to encode airline business logic into modeling and pipelines.

Build and maintain scalable ML models and data pipelines, ensuring data quality for training and inference. Implement MLOps practices using orchestration, containerization, and distributed systems to support data science workflows.

Build and maintain scalable ML models and data pipelines for training and inference. Ensure data accuracy and efficiency across structured and unstructured sources, work with orchestration, containerization, and distributed systems to support production ML workflows and collaboration with data science teams.

Build and maintain ML models and data pipelines to support training and inference. Ensure data accuracy, consistency, scalability, and efficiency across structured and unstructured sources using orchestration, distributed systems, and containerized deployments.

Serve as primary client contact for strategic accounts, drive satisfaction and commercial performance, translate business goals into plans, identify upsell opportunities, support renewals, coordinate cross-functional delivery, analyze client metrics, and represent client needs to influence product and service improvements. Willingness to travel for meetings and events.

Lead strategic relationships with enterprise clients, ensuring satisfaction, commercial performance, product adoption, renewals, and cross-sell. Coordinate internal teams to deliver solutions, monitor performance metrics, provide insights, and represent client needs to influence product and service improvements. Travel for client meetings and events as needed.

Architect and build a self-service, Kubernetes-native platform: implement controllers/operators, everything-as-code (Terraform/Helm/GitOps), enable secure automated developer workflows, and own production reliability, observability, SLOs, and incident postmortems.

Provide frontline technical support for data pipelines and the Fetcherr platform, monitor production workflows, troubleshoot data-related issues, communicate with stakeholders, maintain production schedules and records, and coordinate with Data, R&D, and Product teams to ensure SLA compliance.

Manage strategic enterprise accounts as primary client contact, ensuring satisfaction, commercial performance, renewals, product adoption, and alignment with client objectives. Coordinate cross-functional teams, analyze client metrics, identify upsell/cross-sell opportunities, influence product development with client feedback, and travel for meetings and QBRs.

Build and deploy econometric and ML models for demand forecasting, research novel approaches to improve accuracy and scalability, collaborate with product and engineering to productionize models, and communicate technical findings to non-technical stakeholders.