Head of Data Science (& AI Lead/Co-Founder)

Role Overview

We’re launching an internal AI/LLM venture and seeking a true co-founder who will lead our technical vision, drive product development, and build a world-class data science practice. You’ll partner directly with leadership, own the roadmap for th products, and help spin out a high-growth AI startup from within our organization.

Key Responsibilities

• Technical Leadership: Define and execute the end-to-end AI/LLM technical strategy—from data ingestion and model selection to fine-tuning, scaling, and deployment.
• Product Development: Collaborate with product management to translate market needs into AI features; prototype rapidly and move to production.
• Team Building: Recruit, mentor, and manage data scientists, ML engineers, and AI researchers. Establish best practices for MLOps, A/B testing, and monitoring.
• Incubation & Operations: Set up infrastructure, tooling, and processes to support agile experimentation and continuous iteration within the incubator.
• Stakeholder Alignment: Present technical plans, milestones, and trade-offs to executive sponsors; coordinate with legal, security, and compliance for data governance.
• Go-to-Market Support: Work alongside go-to-market teams to craft demos, pilot programs, and proofs-of-concept that showcase our LLM capabilities to early customers.
• Equity & Ownership: Act as a true co-founder with an equity stake—aligning long-term incentives on growth, fundraising, and exit strategies.

Required Qualifications

• Proven Co-Founder/Leadership Experience: Founded or co-founded at least one AI or data-centric startup, or led a ground-up AI initiative with demonstrable impact.
• Deep Data Science Expertise: Example: Master’s or PhD in Computer Science, Statistics, or related field; 3+ years in data science or ML engineering roles.
• LLM Mastery: Hands-on experience fine-tuning, evaluating, and deploying large-language models (e.g., GPT, LLaMA, Mistral) at scale.
• Production-Grade ML Ops: Expertise with infrastructure (Kubernetes, Docker), data pipelines (Airflow, Prefect), and model-serving frameworks (TensorFlow Serving, TorchServe).
• Cross-Functional Collaboration: Track record partnering with product, design, and commercial teams to ship AI-driven features under tight timelines.
• Fundraising Savvy: Comfortable presenting technical vision to investors and participating in pitch decks, due diligence, and board meetings.

Preferred Experience

• Successful exit or fundraising round in an AI-focused venture
• Open-source contributions in NLP or ML communities.
• Familiarity with prompt engineering frameworks and evaluation metrics for generative AI.

What We Offer

• Equity & Co-Founder Status: Significant founder equity in the new venture alongside a competitive salary.
• Autonomy & Resources: Backing from our parent company’s engineering, design, and go-to-market teams plus a dedicated R&D budget.
• Growth & Impact: A rare opportunity to incubate a cutting-edge business from day one and shape the future of AI within a growing organization.