Pick a Forecasting Stack for an Edtech Engagement Team
Overview
What this challenge is about.
You will produce a 6-page strategy memo evaluating three paths: (1) in-house forecasting team (2 engineers), (2) open-source stack (statsforecast + neuralforecast), (3) forecasting SaaS vendor. For each, estimate first-year cost (in INR and USD), staffing, expected accuracy on a representative cohort, vendor lock-in, and operating risk. Run a small accuracy spike on a one-cohort sample comparing one in-house model vs. the OSS stack. Deliver the memo, the spike notebook, and a 1-page exec summary.
The Brief
What you'll do, and what you'll demonstrate.
Recommend the forecasting stack (in-house vs. OSS vs. SaaS) that gives the best 18-month outcome on cost, accuracy, and lock-in.
Earning criteria — what you'll demonstrate
- Compare build/buy/OSS paths for a forecasting capability
- Estimate first-year cost and staffing for each path
- Run a small accuracy spike to ground the strategy in data
- Communicate a methodology recommendation to executive leadership
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
Careers
Roles this prepares you for.
Real titles. Real skill bridges. Pick the one closest to your trajectory.
AI Product Manager
Producing a defensible build/buy/OSS strategy memo for a forecasting capability is core AI PM work at any scaled product company.
This challenge sharpens
- ai-strategy
- build-vs-buy-analysis
- vendor-evaluation
AI Solutions Architect
Architecting build/buy/OSS choices across cost and lock-in is the solutions architect's textbook job.
This challenge sharpens
- build-vs-buy-analysis
- vendor-evaluation
- cost-estimation
Data Scientist
Running an accuracy spike to anchor a strategy memo is a senior data-scientist contribution to product strategy.
This challenge sharpens
- forecasting-evaluation
- ai-strategy
- data-storytelling