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# VP Data Technology Transformation

- **Company:** Client Server
- **Location:** London, UK (Remote available)
- **Salary:** £120,000.0 - £150,000.0
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Microsoft Azure, Cyber Security, Data Governance, Python (Programming Language), Tensorflow, Google Cloud, Cloud Platform System, Pytorch, Data Strategy, Scikit Learn, Software Library
- **Published:** September 3, 2026
- **Apply:** https://www.client-server.com//job/vp-data-technology-transformation-private-equity/apply

## About the Role

* You have experience in a similar VP of Data / Head of Data role within financial services / consulting with a focus on data diligence, value creation and execution
 * You have a strong technical background including Python, Cloud environments (AWS, Azure, GCP) and modern Machine Learning libraries (e.g. PyTorch, TensorFlow, Scikit)
 * You have advanced experience in conducting data maturity assessments and developing data strategies that drive business transformation and measurable outcomes
 * You have a deep knowledge of data governance frameworks e.g. GDPR, CCPA with experience of ensuring data and information security
 * You have excellent communication and stakeholder management skills, you're able to translate complex technical and data aspects to c-suite investors and push back if necessary
 * You're degree educated in a STEM discipline

## Description

Opportunity to join a massively profitable Private Equity firm that invest in businesses across the finance and insurance space, in an impactful and rewarding Head of Data role.

As the VP Data Technology Transformation, you'll be responsible for leading data strategy, diligence and execution across the fund and its portfolio of companies, working closely with c-suite level investors and data technology counterparts to align strategies, drive efficiencies, scale, optimise systems and identify opportunities for monetisation.

You'll lead the data diligence efforts, create detailed value creation plans, conduct thorough data maturity assessments, track the progress of data initiatives and implement critical data strategies to drive operational improvements and innovation.


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