Janus Henderson

About the role

Hermetic AI is an early-stage startup where data science directly shapes product direction and user outcomes. We’re hiring a Senior Data Scientist to drive deep product analytics, design data models that enable learning loops, and build production ML systems—especially scoring/classification models and text-based LLM applications.

You’ll partner day-to-day with our product team, and the development team to uncover patterns in our data, improve how we measure what matters, and ship models that improve themselves over time.

What you’ll do

• Analyze and diagnose: Explore current datasets to surface product insights, spot patterns/anomalies, and recommend concrete product or instrumentation changes.

• Design the data model: Define/iterate the product data model to ensure we capture the features and labels needed to power self-learning components.

• Build ML systems end-to-end: Own scoring systems and classification pipelines from idea → experimentation → evaluation → production, including monitoring and iteration.

• LLM applications: Develop applied ML for text-based LLM use cases (e.g., supervision signals, feedback loops, heuristics for self-improvement).

• Experimentation & evaluation: Design A/B tests, establish success metrics, run offline/online evaluation, and communicate results clearly to stakeholders.

• Partner across product & eng: Translate ambiguous product questions into data/ML plans and ship pragmatic solutions on tight feedback cycles.

What you’ll bring

• 7+ years in data science or ML roles with shipped, end-to-end production projects.

• Strong data analysis chops: exploratory analysis, feature discovery, pattern finding, and clear storytelling with data.

• Proven experience with scoring systems and classification models (design, training, calibration, and monitoring).

• Hands-on with text-based LLM problems (fine-tuning, evaluation strategies, or leveraging LLMs as components).

• Tooling (must-have): Python, SQL, pandas, scikit-learn.

• Nice to have: AWS and SageMaker.

• Ability to define data models/metrics that align to product outcomes; thoughtful approach to experiment design and causality pitfalls.

• Clear communication, product sense, and a bias to ship.

How we work

• Start-up environment: Small, sharp team (~10 developers). You’ll own meaningful surface area and see your work ship fast.

• Collaboration: Tight loop with the CPO, CAIO, and engineering to align modeling decisions with product goals.

• Remote-friendly: Collaborate synchronously within US Eastern/Central time.

Qualifications

• Preferred: MSc in a quantitative field.
• Portfolio welcome: Links to GitHub, case studies, or write-ups of shipped ML projects.

Job Type: Full-time

Benefits:

• 401(k)
• Health insurance
• Paid time off

Work Location: Remote