Nubank

Financial Services

AIResearchManager

$324k+ Palo Alto, California, United States FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Manager candidates.

The Brief

“AI Research Manager at Nubank. Skills: AI Research, Machine Learning, People Management, Research Operations. Lead, mentor, and advocate for researchers. Foster psychological safety, high ambition, and scientific inquiry”

What You'll Achieve.

Make exceptional science happen; Researchers do great work; Compounding into production capabilities; Build the intelligence layer; See bets reach customers

Industry & Context.

Financial Services
Problems you'll solve

Problem framing; Root cause analysis

What They're Looking For.

Must Have

3+ years people-management experience, M.S. or Ph.D. in quantitative field, Working understanding of core AI methodologies, Build, scale, and retain high-performing teams

Nice to Have

Deep conceptual familiarity with core research areas, Experience operating in global, distributed teams, Experience from foundational research to production systems, GCP Professional Data Engineer, AWS Data Analytics, Databricks Certified, dbt Certified

What You'll Do.

and advocate for researchers

Foster psychological safety

and scientific inquiry

Own operating health of the team

Attract and retain top-tier research talent

Build team reputation

Own operating cadence of research bets

Frame problems and set OKRs

Track progress and make go/no-go decisions

Allocate GPU capacity

Balance exploration against compounding bets

Protect deep-focus research time

Create space for rigorous

Pursue ambitious bets

Raise bar on research rigor and communication

Ensure experimental design

Cultivate team standing in research community

open-source contribution

and conference presence

Partner with senior technical leads

Align operational execution with research roadmap

Ensure clean handoffs from research into production

Translate technical progress into high-impact narratives

Connect research milestones to business outcomes

Bridge foundational research and business strategy

Enable Nubank's AI-first direction

How You'll Work.

Team & Collaboration

Partner with senior technical leads; Cross-functional collaboration; Handoffs from research into production; Collaboration with applied teams; Collaboration with executive leadership

Communication Scope

Executive presentations; Technical communication; High-impact narratives

Process & Methodology

OKRs, Progress tracking, Resource allocation

Full Job Description

AI Research Manager About Nubank Nubank is one of the world's largest digital financial services platforms, recognized by Time 100, Fast Company, and Forbes for leading an industry transformation. Driven by our mission to fight complexity and empower more than 130 million customers, we leverage data and proprietary technology to build the future of financial services. Listed on the New York Stock Exchange (NYSE: NU), we combine proprietary technology, data intelligence, and an efficient operating model to deliver financial products that are simple, accessible, and human. We are executing an AI-first transformation. The AI Core Research team owns Nubank's forward-looking research agenda: the foundational capabilities that compound into long-term advantage rather than incremental wins. The quality of this team directly shapes whether we lead or follow over the next 24 months. About the role As AI Research Manager, you will own the operating health and execution of Nubank's ML research agenda. This is a dedicated people-management role for a small, high-talent-density team of world-class researchers, partnering closely with senior technical leads who drive the scientific direction. The team works on a portfolio of research bets on a one-to-four-quarter horizon. This work compounds into the production capabilities Nubank will depend on. Current and upcoming bets include: Next-generation nuFormer architectures: proprietary transformers that learn from raw transaction sequences and power key production credit decisions Multitask and multi-target modeling: single models serving many high-impact prediction tasks at once Training and inference efficiency: distillation, quantization, sparsity, and parallelism to run state-of-the-art models economically at our scale Causal modeling and policy optimization: moving beyond prediction to the decisions and policies those predictions should drive World models: open-ended models that reason about a customer's full financial life Reco

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