Remote Position29.01.26
AI SCORE 8.5

Head of Data Science - AI Startup

$250K–$300K/year

About the Role

We are seeking a visionary Head of Data Science to join our stealth-mode AI startup. This is a unique opportunity to lead the data function from the ground up and drive innovation in next-generation intelligence solutions. As the inaugural Head of Data Science, you will report directly to the Founder/CEO and play a pivotal role in shaping our AI/data strategy.

What You'll Do

  • Shape and execute the full data science & ML roadmap, from foundational models to advanced production AI systems.
  • Architect scalable data infrastructure, pipelines, and experimentation frameworks to support cutting-edge AI development.
  • Collaborate intimately with the founder on technical vision, rapid prototyping, model iteration, and product direction.
  • Lead talent acquisition and team building: hire, mentor, and scale a world-class data science/ML organization as the company grows.
  • Ensure rigorous best practices around model performance, ethical AI, bias mitigation, explainability, and data governance/security.
  • Drive data-informed decisions that accelerate innovation across engineering, product, and business priorities.

Requirements

  • 7+ years in data science/machine learning, with 3+ years in senior/leadership roles at startups, AI labs, or high-growth tech companies.
  • Deep hands-on experience building and deploying production-grade ML/AI systems (e.g., large-scale models, generative AI, reinforcement learning, multimodal systems, or agentic architectures).
  • Strong technical fluency: Python, SQL, cloud platforms (AWS/GCP/Azure), modern frameworks (PyTorch, TensorFlow, JAX, etc.), and MLOps tools.
  • Proven track record scaling data/ML teams from early stage (0–few) through growth phases, including direct hiring and culture-setting experience.
  • Thrives in ambiguity and fast iteration; excellent at distilling complex technical concepts for founder/exec alignment.
  • Genuine excitement for frontier AI and building transformative technologies from the ground floor.

Nice to Have

  • Experience with generative AI and reinforcement learning.
  • Familiarity with data governance and ethical AI practices.
  • Previous experience in a stealth-mode startup environment.

What We Offer

  • Competitive salary range of $250K–$300K+ base.
  • Significant equity in a high-potential startup.
  • Comprehensive relocation package to help you settle in Austin, TX.
  • Opportunity to work in a thriving AI/tech ecosystem with access to top talent.
  • High-autonomy environment with the chance to make a significant impact.
Why This Job8.5 of 10

This role offers a unique opportunity to lead data science at a pioneering AI startup, with a competitive salary and significant equity.

Salary Range
Required
0/1
Optional
0/1
Bonus
0/1

Who Will Succeed Here

Deep expertise in Python and experience with machine learning frameworks like PyTorch and TensorFlow, allowing for the development of robust AI models and algorithms.

A strong background in cloud platforms (AWS, GCP, Azure) and MLOps practices to efficiently deploy and manage machine learning models in a scalable manner, particularly in a fully remote work environment.

Proven leadership experience in building and mentoring data science teams, with a strategic mindset to align data initiatives with business goals, especially in a fast-paced startup culture.

Learning Resources

Python for Data Science Handbookguide

Career Path

Head of Data Science(Now)Director of Data Science(2-4 years)Chief Data Officer(5-7 years)

Market Overview

Market Size 2024
$15.7B
Annual Growth
21.5%
AI Adoption
75%
Investment
+150%
Labour Demand
+40%
Avg Salary
$180K

Skills & Requirements

Required
PythonSQLAWS
Growing in Demand
Deep LearningData EngineeringCloud ML Services
Declining
R ProgrammingHadoop

Domain Trends

Increased Investment in AI Startups
Venture capital investment in AI startups reached $40B in 2023, a 60% increase from 2022, driving demand for skilled data science leaders.
Shift Towards MLOps Practices
Companies adopting MLOps practices have seen a 30% reduction in deployment time, emphasizing the need for leaders skilled in MLOps.
Growing Use of Federated Learning
Federated learning adoption has increased by 50% in 2023, highlighting a trend towards decentralized data processing, which requires advanced data science capabilities.

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