Drive data-driven co-ordination and execution intelligence for IC development — across analog, digital, verification, layout and validation, in collaboration with Design Controllers, Program Managers, technical project leads and mixed-signal project teams.Support technical co-ordination through planning, reviewing and action tracking, while actively building the analytics, automation and AI foundation that scales the project management Methodology and powers a data-driven Lessons Learned process.Principal Accountabilities: Capture overall Task Planning for design and verification based on Design Control Methodology and guidance from senior peers.Perform data rollup, analytics and visualization, including weekly project status, resource distribution, and portfolio health, as input to functional leads and other Design Controllers.Build, maintain and continuously improve Power BI dashboards, Power Query / DAX models, and Jira-based data pipelines that underpin the DC reporting suiteCapture and maintain project metrics rolling up into the Project Register. Detect, highlight and explain deviations from leading and lagging execution indicators, using both descriptive and predictive analytics.Prototype and support AI / GenAI / agentic use-cases that augment Design Control execution- for example, automated executive summaries, anomaly detection on milestone drift, and conversational drill-downs into project data.Use Post-Project-Analysis to feed a data-driven Lessons Learned process and drive continuous improvement of the Design Control Methodology.Partner with adjacent functions (PMO, MDP, Jira admins) to help centralize and standardize the DC data layer across projects.Other tasks relevant to the position as deemed reasonable by your manager.Key Performance Measures: Accurate technical planning and reporting for small-to-mid-scale IC development, delivered to the required quality and industry standards.Increased adoption and quality of DC metrics (leading + lagging indicators) in project planning, tracking and executive reporting.Reduction in manual reporting effort through automation of data pipelines, dashboards and recurring analyses.Tangible AI / analytics proofs-of-value delivered against the DC roadmap (e.g., automated exec summaries, drift/anomaly detection, portfolio-level insights).Data-driven Lessons Learned process is effective, with clear, actionable continuous-improvement outcomes.Technical meetings are effective with clear outcomes and deliverables.
