About HBX Group
HBX Group is the world's leading technology partner, connecting and empowering the world of travel. We're game-changers, disruptors, the people who bring together local and global brands in accommodation, transport, activities and payments through our network of 300,000 hotels worldwide, 60,000 hard to reach high value clients such as tour operators, travel agents and loyalty schemes across 140 source markets. We are tech-driven, with a customer-first philosophy, and commercial teams whose knowledge and relationships on the ground are second to none.
Responsibilities
•Own end-to-end responsibility of the Sourcing Domain services, ensuring alignment with business objectives and technology strategy.
•Lead the design and delivery of Data, ML and AI solutions that support supplier acquisition, commercial performance, revenue growth and operational excellence.
•Ensure all IOS solutions are scalable, reliable, maintainable and aligned with business priorities and company strategy.
•Act as the senior technology authority for the Sourcing domain, defining engineering standards, architectural principles and solution design best practices.
•Drive the continuous evolution of data-driven capabilities across the domain, identifying opportunities to increase automation, efficiency and business value.
•Ensure platform scalability, reliability, security, maintainability and cost-efficiency as business demand grows.
•Build strong relationships across Product, Data Science, Engineering and Business teams to ensure alignment and successful execution, communicating strategy, progress, risks and investment requirements effectively to senior stakeholders.
•Assume end-to-end ownership of sourcing data services and solutions operating in analytics production environments.
•Ensure the reliability, performance and availability of business-critical analytical, ML and AI services.
•Establish and monitor service KPIs, operational metrics and performance indicators within their responsibilities.
•Lead incident resolution, root cause analysis and continuous improvement initiatives when production issues occur.
•Ensure operational readiness and long-term sustainability of all delivered solutions.
•Promote experimentation and innovation while ensuring solutions deliver measurable business value.
•Drive adoption of advanced AI techniques, optimization algorithms and intelligent decision-making capabilities across the organization.
Requirements
•Exceptional leadership skills with proven ability to lead multiple engineering teams through Team Leads and senior technical contributors.
•Strong stakeholder management capabilities, with experience engaging and influencing Director and C-Level stakeholders.
•Strong business acumen with the ability to understand commercial challenges and translate them into scalable Data, Analytics, Machine Learning and AI solutions.
•Outstanding communication and presentation skills, capable of explaining complex technical concepts to both technical and non-technical audiences.
•Strategic mindset with the ability to align technology investments and engineering priorities with business objectives.
•Proven ability to lead large-scale, cross-functional initiatives involving Engineering, Product, Data Science and Business teams.
•Strong decision-making and prioritization skills in fast-paced environments with competing priorities.
•Ability to balance innovation, experimentation and long-term platform sustainability.
•Strong people leadership capabilities, including coaching, mentoring and capability development.
•Demonstrated experience building high-performing engineering organizations and fostering a culture of ownership and continuous improvement.
•Excellent analytical and problem-solving skills.
•Resilience and ability to operate effectively under pressure while managing business-critical initiatives.
•Strong command of English, both written and verbal.
•Deep understanding of Machine Learning, Artificial Intelligence and predictive analytics solutions in production environments.
•Experience delivering and scaling business-critical ML and AI solutions that generate measurable business impact.
•Strong understanding of supervised and unsupervised learning techniques, recommendation systems, optimization algorithms and predictive modelling.
•Familiarity with Generative AI concepts, LLM-based solutions and AI-assisted decision-making systems.
•Proven experience building, deploying and operating Machine Learning solutions in production.
•Strong understanding of MLOps practices including model deployment, monitoring, retraining, versioning and lifecycle management.
•Experience designing scalable ML pipelines and automated model delivery frameworks.
•Experience implementing observability, performance monitoring and reliability controls for production ML services.
•Strong understanding of modern data architectures supporting Analytics, ML and AI workloads.
•Experience working with cloud-based analytical ecosystems including Snowflake, dbt and modern ELT frameworks.
•Strong knowledge of data integration patterns including batch, streaming, APIs and event-driven architectures.
•Experience supporting enterprise analytical platforms and data products consumed by multiple business domains.
Conditions
No conditions stated in the posting.
