# Ville Brofeldt

> Data Platform at Apple, PMC at Apache Superset

Location: San Francisco Bay Area, United States
Profile: https://flows.cv/ville

Passionate about data visualization and engineering, machine learning, open source and endurance sports. Apache Superset committer / PMC member.

## Work Experience
### Staff Software Engineer @ Apple
Jan 2025 – Present | Cupertino, California, United States
Part of the Data Platform team at Apple, one of the lead engineers for an internal analytics service built in part on Apache Superset. Responsible for the design and operation of a Kubernetes Operator (Golang, Operator SDK) that manages the service, as well as multiple OAuth2/OIDC integrations. Actively contributing to Apache Superset Extension framework and promoting OSS internally.

Org: Apple Services Engineering (previously: Apple Cloud Services)

### Senior Software Engineer @ Apple
Jan 2022 – Jan 2025 | Cupertino, California, United States

### Committer, Apache ECharts @ The Apache Software Foundation
Jan 2021 – Present

### Committer & PMC, Apache Superset @ The Apache Software Foundation
Jan 2019 – Present

### Staff Software Engineer @ Preset
Jan 2020 – Jan 2022 | San Mateo, California, United States
Help building a data visualization SaaS company around Apache Superset. Notable achievements include ramping up product from pre-customer phase to fully generally available product and being one of the main contributors to the Apache Superset project as contributor, community representative and release manager.

### Head of Data and Analytics @ Aktia
Jan 2017 – Jan 2020 | Helsinki, Finland
Worked on upgrading data architecture and related integrations from on-prem to cloud and expanding use of self service reporting.

### Credit Risk Manager @ Aktia
Jan 2009 – Jan 2017 | Helsinki, Finland
Responsible for group-wide credit risk quantification, mainly using IRB-type models. Main activities included credit data ETL, model development and validation, credit risk reporting, capital calculations (internal + regulatory), stress testing and risk-based pricing. IRB models received regulatory approval for IRB risk quantification purposes.

Models: Internal Ratings Based Approach (IRB): Probability of Default (PD), Loss Given Default (LGD), Exposure At Default (EAD), IFRS9 12 month and Lifetime Expected Credit Loss (ECL).
Modelling methodology: Linear and Logistic Regression, Random Forest, GBM, Bayesian statistics.
Main tech: R, Python, .NET, SQL, SSIS, SQL Server, Oracle.

### Credit Risk Analyst @ OP-Pohjola Group
Jan 2006 – Jan 2009 | Helsinki, Finland
Development and validation of IRB models, Economic Capital, stress testing and risk based pricing. Models later received regulatory approval for use in Internal Risk Based Approach (IRB) capital adequacy calculations for both retail and corporate portfolios.
Some tech: Java, R, Base SAS.

### Financial Engineer @ CD Financial Technology
Jan 2004 – Jan 2006 | Helsinki, Southern Finland, Finland
Development of Value-at-Risk (VaR) and yield curve estimation models for bond and derivative portfolios. The software was developed using C/C++ and Java, with some applications in Excel/VBA.


## Education
### M.Sc. in Finance, Computer Science, Statistics
Hanken School of Economics

### Information Technology
The University of Manchester Institute of Science and Technology (U


## Contact & Social
- LinkedIn: https://linkedin.com/in/villevbro
- Portfolio: https://twitter.com/VilleVBro
- GitHub: https://github.com/villebro

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Source: https://flows.cv/ville
JSON Resume: https://flows.cv/ville/resume.json
Last updated: 2026-04-12