Drishti Idnani - Portfolio

Oct 2023 - Present

• Own the entire U.S. data infrastructure, designing backend systems and foundational data sources used in 30+ dashboards for daily and strategic decisions.
• Rebuilt the SARIMAX forecasting model, integrating GDP and TAM to drive a 17% improvement in accuracy and optimize financial planning.
• Built real-time ETL pipelines for key KPIs like Revenue, PnL, and channel performance — cutting manual reporting by 40% and accelerating executive insights.
• Trained 10+ colleagues in Power BI, enabling cross-functional teams to build and maintain dashboards that have supported over $100M+ in business decisions.
• Partner with global stakeholders across product, sales, and supply chain to drive a data-first, automation-centric culture.

At ASUS, I don’t just analyze data — I’ve built the backbone of how data powers decisions across the U.S. business.

Oct 2022 - Sep 2023

• Spearheaded 25+ automation initiatives across planning, supply chain, and finance—saving 3,500+ hours annually by replacing manual processes with scalable Python/SQL pipelines.
• Designed a SARIMAX-based forecasting model with 82% accuracy, enhancing supplier reliability and strengthening alignment with global partners.
• Built a centralized data repository by merging fragmented sources, improving data accessibility and speeding up decision-making across the org.
• Mentored cross-functional teams in Python, SQL, and visualization tools, enabling them to independently build and automate analytics solutions.
• Enabled repeatable data workflows that supported multi-million dollar product planning decisions across the NUC portfolio.

I empowered Intel’s teams to shift from reactive to proactive — through automation, mentoring, and smarter forecasting.

Feb 2022 - July 2022

• Designed and deployed an end-to-end data pipeline for Supply Chain Shortages reporting, reducing inconsistencies and standardizing outputs across teams.
• Automated allocation utilization tracking and created a dynamic supply dashboard, saving 2.5+ hours/week per planner and improving visibility for operational leaders.
• Partnered with global planning teams to implement reporting solutions that aligned with real-world bottlenecks and evolving business needs.
• Delivered production-grade work as an intern — many of which became permanent components of Intel’s planning system post-internship.

“Even as an intern, I delivered scalable, real-time solutions that stuck.”

Computer & Information Science & Engineering, 2021–2022

• Focus: Data Science, Machine Learning, Systems
• Specialized in data science, forecasting, and applied machine learning with a focus on practical business impact.
• Developed forecasting and analytics projects that informed later work at Intel and ASUS — bridging academic theory with real-world implementation.

My master’s experience gave me a strong foundation in building explainable models, working with messy data, and integrating business context into analytics solutions.

July 2020 - December 2020

• Designed and deployed an end-to-end data pipeline for Supply Chain Shortages reporting, reducing inconsistencies and standardizing outputs across teams.
• Automated allocation utilization tracking and created a dynamic supply dashboard, saving 2.5+ hours/week per planner and improving visibility for operational leaders.
• Partnered with global planning teams to implement reporting solutions that aligned with real-world bottlenecks and evolving business needs.
• Delivered production-grade work as an intern — many of which became permanent components of Intel’s planning system post-internship.

“Even as an intern, I delivered scalable, real-time solutions that stuck.”

Computer Engineering, 2016-2020

• Focus: Computer Engineering, Data Science, Python
• Conducted research on encryption technologies and online testing during Covid times, co-authoring two papers that were published in international journals/conferences.
• Final-year project applied machine learning and NLP techniques, demonstrating early interest in building interpretable, scalable systems.

My undergrad experience helped build a strong foundation in computer systems, data structures, SQL, Python, and full-stack development, which formed the basis of your later data science work.