In episode 3 of "AI and ML Conversations," I sit down with Diogo, a senior data scientist at Usercentrics and a PhD researcher in data science, to unpack pragmatic data science, marketing measurement, and using LLMs with strong privacy guardrails.​Diogo traces his path from management and marketing into industry roles across Europe, balancing a remote career in Norway with research on measuring cultural value - drawing sharp parallels to brand equity, data scarcity, and business value.​We cover what it takes to be effective with quick proofs of concept, financial value proxies, and privacy-first use of LLMs for customer data enrichment.The conversation also dives into remote vs office culture across countries, startup realities where roles blur across data and engineering, and lightweight rituals like bi‑weekly project reviews that keep stakeholders aligned and accountable.​Timestamps​00:00 - Introduction​00:40 - Guest intro: Diogo, background, Usercentrics​01:13 - Why a PhD and timing trade‑offs​05:02 - Cultural economics: measuring cultural value vs brand equity​07:41 - Data scarcity and useful variables: ticketing API, weather/holidays, telco footfall, surveys​09:19 - Economic impact: spillovers to housing and tourism; online reviews sentiment​11:59 - Moving from Portugal to Norway; EOR setup and distributed teams​13:15 - Remote vs office: flexibility, productivity, and policy pitfalls​16:55 - Portugal’s remote reality, expats, and housing pressure​19:04 - Ship value fast: POCs, value rules, pragmatic LTV signals​23:49 - Communicating with non‑technical stakeholders and focusing on business metrics​27:18 - Startup roles: DS, DE, MLE, AI eng; wearing multiple hats​30:34 - Meetings and ceremonies: beyond daily standups to bi‑weekly project cadences​34:57 - Toolbox: VS Code, schemas, and data discoverability pains​36:59 - The measurement trifecta: attribution, geo‑incrementality, and Marketing Mix Modelling (MMM​)39:35 - Adding external signals (e.g., Apple keynotes) to MMM​40:29 - LLMs for customer data enrichment and segmentation​42:26 - Hosting models on Vertex AI/Azure and privacy considerations​43:09 - Career advice: build close stakeholder relationships and iterate visibly​44:56 - Closing​

Ver todos los episodios