Build and maintain analytical models for the identification, classification, and monitoring of social, environmental, climate, and reputational risks — cross-referencing public and internal databases.
Develop composite indices, scorings, and exposure metrics that support risk frameworks and governance decisions across Nu's operating geographies.
Automate the collection, processing, and visualization of recurring team data — reducing rework and increasing the area's response capacity.
Support the development of KRIs (Key Risk Indicators) and monitoring dashboards for the Sustainability Risk and Reputational Risk verticals.
Contribute to thematic analyses and post-mortems of risk events, transforming raw data into risk management narratives for internal stakeholders.
Lead cross-geo projects autonomously, managing multiple stakeholders and delivering scalable outputs across all geographies.
Qualifications
Degree in Statistics, Data Science, Economics, Engineering, Environmental Management, Communications, Actuarial Sciences, or fields with a strong quantitative component.
Experience in regulated environments or in projects interfacing with compliance and governance.
Knowledge of or interest in sustainability, climate, ESG, and reputational management topics — whether through academic background, previous projects, or personal interest.
Experience with public and heterogeneous data (geospatial, time series, socioeconomic data, text analysis for narrative monitoring and public perception) — knowing where to source it, how to process it, how to cross-reference it with internal databases, and how to interpret results.
Fluent English for written and verbal communication in a cross-geo environment.
Experience with NLP, credit, and customer data. Familiarity with public climate and social databases (e.g. IBGE, EM-DAT, MapBiomas, GDELT, INMET).
Proficiency in Python or R for data analysis, modeling, and automation — with experience in large dataset manipulation and building analytical pipelines. Prior exposure to risk contexts (credit, market, operational).
Ability to structure ambiguous problems: translating a business or risk question into an applicable analytical methodology.
Location & Work Model
Hybrid 2-3 times/week: Our hybrid work model brings us to the office at least twice a week, on strategic days designed to maximize team connection and collaboration.