sandeep kaur

AI, machine learning, and data analytics and digital transformation
programmes.
• Scoped analytical product requirements for AI-powered client solutions, translating business problems into technical
specifications across ingestion, transformation, and output layers.
• Advised clients on ML and predictive-analytics adoption, identifying use cases and guiding evidence-based decision
making.
• Led cross-functional alignment between engineering, data, and commercial stakeholders to ship analytical products on
time against strategic objectives.
• Conducted data quality audits within client environments, diagnosed pipeline failures, and defined remediation roadmaps
that restored stakeholder trust.
• Designed process automation strategies for repetitive data workflows, reducing manual overhead for client teams.

Global aviation serving airlines, airports, travel, and financial institutions.
• Led strategic reset of a declining sales-facing data product, managing discovery, stakeholder engagement, and delivery
across four cross-functional teams simultaneously.
• Reframed senior leaderships understanding of product success, shifting the mental model from data-driven automation
to high-noise, low-value signal system, directly changing programme objectives.
• Influenced leadership to discontinue 8 of 11 data alerts, eliminating decision overload and restoring organisational trust
in data insights.
• Redirected programme strategy from real-time alerts to a prioritisation-led insights dashboard, realigning the roadmap to
quarterly account-planning cycles.
• Developed a reusable decision-quality framework adopted internally; delivered training sessions and 3 speaking events at
UK universities on AI and data literacy.

Travel-tech startup offering personalised trip planning and booking solutions.
• Challenged founder assumptions on large-scale data aggregation feasibility through structured cost, risk, and dependency
analysis, preventing a premature product build.
• Defined a phased roadmap aligning ambition with resource reality and technical constraints.

Government R&D institution focused on defence technologies and advanced analytics. (Healthcare ML Research)
• Built an early-stage image-recognition prototype to detect melanoma indicators from skin images.
• Curated datasets and tested ML models, identifying data quality and diversity as key accuracy constraints; shifting team
expectations from quick prototype to real-world clinical requirements.