Meet the Team
The Forecasting Team within Global Planning is pioneering the application of Causal AI to deliver resilient, explainable, and actionable demand forecasts, where traditional forecasting has struggled during structural market changes, supply disruptions, and shifts in customer behavior. The team publishes bookings, cost, and unit forecasts for more than 10,000 hardware products; giving Demand Planners a trusted reference, and informing S&OP discussions across Supply Chain, Finance, Marketing, and Sales by quantifying risk through forecast ranges and scenarios.
Your Impact
You will develop a forward-looking view of the economic, technology, and component-market forces shaping demand for Cisco products. You will originate hypotheses, run econometric and causal analysis, challenge conventional narratives, and turn external intelligence into quantitative inputs for Cisco's forecasting models and planning.
This is a global role, with team members in India, Europe, and the Americas, and requires some later working-hour overlap with colleagues.
You Will:
- Build an original, actionable view of the macroeconomic and financial conditions affecting demand for Cisco products and customer segments.
- Form economically grounded hypotheses about the drivers of Cisco demand and test them using econometric and causal-inference methods.
- Apply data science tools to convert external economic and market intelligence into candidate causal features, priors, structural relationships, and model specifications.
- Develop a forward-looking view of market size and growth for Cisco's infrastructure markets, assessing the limitations of vendor surveys, competitor results, and research-provider estimates, and help reconcile data-science forecasts with them.
- Partner with product-modelling teams to link market outlooks to product-level adoption and transition forecasts and distinguish true market expansion from substitution, share shifts, and pulled-forward demand.
- Contribute to an integrated three-year bookings outlook and build baseline, upside and downside supply-chain scenarios to help communicate risks to partners.
- Develop supply-and-demand perspectives on critical component markets (memory, optical components, silicon/ASICs, storage/SSDs, PCBs, CPUs, etc.), covering supplier capacity, capital investment, inventory cycles, concentration, and how AI and other end-market demand affect pricing, availability, and lead times.
- Work closely with business leads and experts in Global Planning, other Supply Chain functions, Finance, and other Cisco organizations to understand relationships and patterns driving Cisco demand.
Minimum Qualifications
- Masters degree, or PhD, in Economics, Quantitative Finance, or a related quantitative field (e.g. Maths, Statistics, or Physics).
- Industry experience working in economic or investment research, financial services, technology-market analysis, or a comparably quantitative environment.
- Proven track record of leading end-to-end analytical projects, owning work products with wide customer impact, and influencing senior partners with your analysis.
- Strong Python skills, with experience sourcing and integrating large external datasets that differ in frequency, definition, publication lag, and granularity.
- Strong practical knowledge of applied time-series analysis, forecasting, and explainable machine learning techniques such as causal inference or SEM.
- Domain knowledge developed in at least one of the following:
-Applied macroeconomic and econometric analysis, with the ability to connect market developments to product outcomes.
-Company financials analysis, including earnings materials, capex plans, alternative data, and financial and economic data platforms.
-Analysis of technology components or other capital-intensive markets (e.g., AI infrastructure, semiconductors, electronic components, data centers, networking).
Preferred Qualifications
- Excellent communication and storytelling skills, able to turn complex analysis into concise narratives, scenarios, and recommendations for non-technical senior customers.
- Intellectual curiosity and the ability to form an independent point of view in an ambiguous, fast-changing environment.
- A PhD or research-oriented Masters with substantial applied econometrics content, and deeper industry experience including London financial-sector roles such as technology or semiconductor research, macro strategy, or investment analysis.
- Advanced expertise in causal discovery, structural causal models, Bayesian methods, econometrics, or nowcasting, applied in time-series settings.
- Experience in semiconductor, memory, optical, ASIC, CPU, storage, PCB, or data-center markets, including an understanding of capacity cycles, supplier economics, lead-time formation, inventory corrections, and component pricing.
- Experience estimating market size, technology adoption, diffusion curves (e.g., Bass), installed-base replacement, or product substitution.
- Proficiency in SQL, Git, and reproducible research practices, with experience delivering production-quality work alongside data scientists.
- Demonstrated record of influencing senior stakeholders and mentoring colleagues, with the confidence to challenge prevailing assumptions using evidence.
Why Cisco?
At Cisco, we’re revolutionizing how data and infrastructure connect and protect organizations in the AI era – and beyond. We’ve been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint.
Fueled by the depth and breadth of our technology, we experiment and create meaningful solutions. Add to that our worldwide network of doers and experts, and you’ll see that the opportunities to grow and build are limitless. We work as a team, collaborating with empathy to make really big things happen on a global scale. Because our solutions are everywhere, our impact is everywhere.
We are Cisco, and our power starts with you.
