We are representing a sector-specialist investment firm that focuses on financial technology companies. With expertise in software, data, and investment services, the firm provides mission-critical products and services across sectors like Banking & Payments, Capital Markets, Data & Analytics, Insurance, and Investment Management. They pursue growth and buyout opportunities in North America and Europe, aiming to accelerate business growth and operational excellence. Their unique approach integrates deep investment experience with operational and innovative capabilities to drive long-term value creation.
The Head of Data will lead data strategy and execution across the fund and its portfolio companies. This role will focus on data-driven initiatives, conducting data maturity assessments, and managing the progress of key projects. The ideal candidate will partner with portfolio companies on data initiatives and collaborate with deal teams to identify investment and partnership opportunities through data asset scanning.
Key Responsibilities
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Data Diligence & Value Creation Planning: Lead data diligence efforts and develop value creation plans to leverage data for business growth and operational improvements.
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Data Maturity Assessments: Conduct regular data maturity assessments across the portfolio, identifying opportunities for improvement and creating roadmaps for enhancing data capabilities.
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Progress Tracking & Execution Support: Oversee the progress of data initiatives and provide execution support to portfolio companies, ensuring alignment with overall business objectives.
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Data Transformation Execution: Collaborate with portfolio companies to implement data strategies that drive innovation and operational improvements.
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Data Asset Scanning for M&A & Partnerships: Identify investment opportunities by analyzing data assets and collaborating with deal teams on potential partnerships.
Qualifications
- Extensive experience in data leadership roles within private equity, venture capital, or investment settings.
- Expertise in data diligence, value creation, and data strategy development for business transformation.
- Hands-on experience with modern machine learning libraries (e.g., TensorFlow, PyTorch) and cloud-based environments (e.g., AWS, Azure).
- Strong understanding of data governance frameworks (e.g., GDPR, CCPA) and experience in ensuring data privacy and compliance.
- Proficiency in building and optimizing data pipelines and driving value from data across diverse business use cases.
- Excellent communication skills, with the ability to convey complex data insights to C-level executives.
Interview Process
- Technical screening
- Case study/technical assessment
- Cultural fit evaluation
- Final interview
