Principal / Senior Data Scientist, Agentic AI

Arlyn AI

New York (NY)

On-site

USD 175,000 - 255,000

Full time

5 days ago
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Benefits offered by this job

Equity grants
Unlimited PTO
Employee benefits package

Job summary

Arlyn AI, a New York-based startup focused on AI-powered insights for life sciences, seeks a Principal/Senior Data Scientist for Agentic AI to transform unstructured data into actionable ontologies and drug-access insights.

You will own end-to-end LLM applications, design production-ready AI systems, and collaborate with Engineering and Data Science to scale infrastructure and improve performance, with on-site work at Hudson Yards, NYC.

Qualifications

  • 5+ years of industry experience in finance, biotech, or tech startups, or a PhD in a quantitative field with 2+ years of industry experience.
  • Hands-on experience building AI applications, including prompt engineering, advanced analytics, and transforming large-scale unstructured data into production-ready solutions.
  • Ability to translate complex, ambiguous business challenges into clear, structured data problems and drive decision-making.

Responsibilities

  • Own the end-to-end development and deployment of agentic LLM applications that deliver measurable business impact.
  • Design, build, evaluate, and ship production-ready AI systems from prototype to production.
  • Partner with founders to define product direction and turn business problems into AI solutions.
  • Collaborate with Engineering to build scalable AI infrastructure, system architecture, and internal tools.
  • Improve system performance, reliability, and user experience through rapid experimentation and iteration.

Job description

Arlyn AI – AI-Powered Insights for Life Science

Arlyn AI is a New York based, fast-growing AI startup expanding patient access to life-changing medicines while reducing commercial costs for drug innovators.

Principal / Senior Data Scientist, Agentic AI

We're looking for a data-driven problem solver to leverage large language models (LLMs) and transform unstructured data into data ontologies and actionable insights that drive drug launches and access strategies. You'll work at the intersection of AI, data science, and healthcare, helping biotech and pharma companies navigate patient access barriers and optimize commercial decisions.

What You’ll Do
  • Own the end-to-end development and deployment of agentic LLM applications that deliver measurable business impact.

  • Design, build, evaluate, and ship production-ready AI systems from prototype to production.

  • Partner with founders to define product direction and turn business problems into AI solutions.

  • Collaborate with Engineering to build scalable AI infrastructure, system architecture, and internal tools.

  • Improve system performance, reliability, and user experience through rapid experimentation and iteration.

What We’re Looking For
  • A strong conceptual thinker with deep technical expertise, who enjoys translating complex, ambiguous business challenges into clear, structured data problems.

  • Passionate about LLMs and real-world AI applications, with a pragmatic, impact-driven mindset

  • Bachelor’s/Master’s degree with 5+ years of industry experience in finance, biotech, or tech startups, Or PhD in a quantitative field (CS, Computational Biology, Statistics, etc.) with 2+ years of industry experience

  • Hands-on experience building AI applications, including prompt engineering, advanced analytics, and transforming large-scale unstructured data into production-ready solutions

  • Collaborate across Engineering and Data Science teams to lead decision-making on essential system architectures and core operational workflows.

Compensation & Benefits

Cash compensation range: $175,000 - $255,000
Equity grants in Arlyn AI
Unlimited PTO
Employee benefits package

Location: Hudson Yards, NYC (on-site 3 days a week)

We’re building in New York and love having the team together in person. If you’re not already based in the area, we’ll support your relocation so you can join us here.

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