AI Analyst

About AppliedXL

AppliedXL is redefining how information powers decisions in the age of AI. As more work flows through machines first, data must be structured, contextual, and trusted. We turn raw noise into machine-readable signals, enabling analysts and AI systems to anticipate events before they happen.

Starting with biotech, life sciences, and healthcare, we surface risks and opportunities weeks ahead of disclosure. Our mission: deliver news before it becomes news,  building the standard for structured intelligence that drives high-stakes decisions in finance, healthcare, and beyond.

By joining AppliedXL, you’ll help create the trusted signals that humans and machines rely on.

The Role

This is not a traditional analyst role. You’ll work at the intersection of data, editorial judgment, and AI. Your job is to uncover patterns, design intelligence feeds, and ensure that every signal is accurate, contextual, and actionable.

You’ll collaborate closely with the Head of GenAI Content and play a key role in refining how humans and AI work together to detect emerging insights. Over time, you’ll take increased ownership of editorial pipelines, signal quality, and content accuracy. This is a high-impact opportunity for someone eager to shape the future of AI-assisted intelligence.

What You’ll Do

Understand

Learn quickly about complex domains such as biotech, pharma, and regulation.

Translate domain complexity and user workflows into clear, useful insights.

Connect data signals to real-world outcomes that matter to investors and biopharma stakeholders.

Internalize AppliedXL’s editorial and signal design philosophy.

Analyze

Explore datasets to identify key trends, anomalies, and shifts over time.

Assess what data changes mean for end users.

Shape editorial hypotheses and maintain a high bar for analytical clarity and explainability.

Generate

Develop and refine AI prompts for editorial and analytical tasks.

Apply domain knowledge to guide AI analysis and generate structured insights.

Collaborate with the Head of GenAI Content to ensure AI outputs meet editorial and analytical standards.

Integrate

Use internal tools and pipelines to turn raw data into structured intelligence.

Understand foundational AI concepts (model reasoning, tokenization, prompt behavior) and apply them in practice.

Partner with product, data, and engineering teams to improve tooling and workflows.

Document and share best practices for scalable AI–editorial collaboration.

What We’re Looking For

Domain fluency in life sciences (biotech, pharma, or clinical trials).

Strong ability to learn new subjects and explain complex ideas clearly.

5+ years of experience in data analysis, content engineering, or applied AI.

Logical mindset; familiarity with Python or SQL is a plus.
Editorial instincts, you know how to question, frame, and contextualize information.

Experience with AI tools such as LLMs, prompt engineering, LangChain, or retrieval-augmented generation (RAG).

Ability to move fluidly between technical detail and strategic impact.

A curious, rigorous thinker who always asks: “What does this data really mean, and why does it matter?”