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Applied AI Data Scientist

  • Source: LinkedIn
  • Haystack
  • Remote
  • New York City
  • Full-Time
  • Mid level

Job Description

We’re working with a global provider of information-based analytics and decision tools for professional and business customers, serving clients in over 150 countries.

The Role

  • Help shape the next generation of AI-powered legal products and experiences by partnering with internal teams and enterprise stakeholders.
  • Design, evaluate, and continuously improve AI capabilities for legal research, drafting, and decision-making.
  • Frame problems, run experiments, design evaluation methodologies, and turn applied research into production-ready AI features.
  • Work at the intersection of AI experimentation, developer enablement, evaluation, and customer engagement.
  • Contribute a data science lens to model selection, retrieval quality, prompting strategy, and measurement.

What You’ll Need

  • 6+ years of experience as a Data Scientist, Applied Scientist, or Machine Learning Engineer with a track record of shipping data-driven solutions.
  • Strong foundation in statistics and experimental design, including hypothesis testing, A/B testing, and causal inference.
  • Strong programming skills in Python (pandas, NumPy, scikit-learn) and SQL for large datasets.
  • Hands-on experience developing and evaluating LLM-powered or machine learning solutions in production settings.
  • Demonstrated ability to design rigorous evaluation methodologies and metrics for AI/ML systems.
  • Practical experience with LLM techniques such as prompting, retrieval-augmented generation (RAG), and embeddings.

What’s On Offer

  • Opportunity to work on cutting-edge AI for legal products.
  • Engage directly with customers to understand and solve their real-world problems.
  • Collaborative environment with AI engineers, machine learning engineers, and product teams.
  • Contribute to the development of next-generation AI capabilities and evaluation standards.

Apply via Haystack today!

Skills

  • Python
  • Pandas
  • NumPy
  • Scikit-learn
  • haystack

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