Fractional CDO / Data Leader

About this opportunity

We are placing Fractional CDOs and Data Leaders with Series A–C companies sitting on valuable product and customer data they cannot yet use. The data is there — unstructured, siloed, and underused. These companies need a senior data operator who can build the stack, define the model, and start shipping data-driven and AI-powered product features.

This is a high-leverage, technical leadership role. You will own the data strategy, build or migrate the data infrastructure, and work side-by-side with product and engineering to turn data into a measurable competitive advantage.

Core responsibilities

• Conduct a data infrastructure audit and define a target-state modern data stack architecture within 30 days
• Design and implement the company's semantic data model — events schema, entity definitions, truth sources, and metric definitions
• Build or migrate to a modern data stack: dbt + Snowflake/BigQuery + Fivetran/Airbyte + Looker/Metabase/PowerBI
• Lead ML engineering — feature store design, model training pipelines, A/B testing frameworks, and production model monitoring
• Evaluate and implement LLM-powered product features: RAG architectures, fine-tuning, prompt engineering, and AI agent workflows
• Establish data governance: access control, data quality SLAs, lineage documentation, and PII handling policies
• Build self-serve analytics capabilities — enabling non-technical stakeholders to answer product, marketing, and finance questions independently
• Ensure compliance with GDPR, CCPA, and any industry-specific data privacy regulations
• Build and lead the first data team: analytics engineers, data scientists, and ML engineers

Required qualifications

• 10+ years in data engineering, data science, or analytics, with at least 4 years in a CDO, VP Data, or equivalent leadership role
• Hands-on experience implementing modern data stacks (dbt, Snowflake, BigQuery, Databricks, or equivalent)
• At least 2 production ML or AI systems shipped in a live product context
• Deep knowledge of data governance, privacy regulation (GDPR/CCPA), and data quality management
• Ability to hire, manage, and develop a data team of 3–10 engineers and scientists
• Executive communication skills — able to translate data strategy into business outcomes for boards and investors

Nice to have

Not required — but will strengthen your match quality.

• Experience with LLM fine-tuning, RAG pipeline design, or AI agent architecture
• Background in Fintech, HealthTech, eCommerce, or marketplace data problems
• PhD or MSc in Statistics, Computer Science, or a related quantitative field
• Prior fractional CDO or advisory data leadership experience

Application process

1. 01Application with one data infrastructure transformation case study: before state, stack decisions, and business impact
2. 0245-minute technical panel — data modelling exercise and ML pipeline design discussion
3. 03Profile approved and matched to active companies
4. 04Founder intro call — data maturity and infrastructure assessment
5. 05Kick-off within 2 weeks