We ask “why” until we get to the root. We explore new ideas, research papers, every single edge case and anything that sharpens our understanding.

We use AI like a second brain. From writing code to writing docs, debugging flows to exploring new ideas, AI is part of our daily rhythm. Everyone here gets hands-on with the tools, learns how to prompt better, and treats AI as a teammate.

Role Description

We are looking for a  Forward Deployed Engineer – Product  to work at the intersection of product, data, and client engagement. This role partners closely with customers and internal product teams to deploy, customize, and operationalize data-driven solutions in real-world commercial environments.

You will combine  analytical problem-solving, data engineering, and product thinking  to translate complex business questions into scalable product features and insights. The role requires hands-on experience with  SQL, data analysis, and modern AI/LLM tools , along with a strong understanding of  pharmaceutical commercial data and analytics workflows . This position is ideal for individuals who enjoy solving ambiguous problems, working closely with clients, and shaping the evolution of a product through real-world deployments.

Client-Facing Product Deployment

• Work directly with clients and internal teams to implement and customize product solutions for commercial analytics use cases.
• Translate client business questions into data models, analyses, and product features.
• Serve as the technical bridge between client teams, product, and engineering.

Data Analysis and Insight Generation

• Write and optimize  SQL queries  to analyze large healthcare and commercial datasets.
• Conduct exploratory data analysis to identify patterns, opportunities, and insights.
• Build analytical workflows that support product capabilities and client needs.

AI-Enabled Analytics

• Use  LLM-based tools and workflows  to accelerate data analysis, insight generation, and knowledge extraction.
• Design prompts and workflows that combine structured data with AI-assisted analysis.
• Support development of AI-enabled analytics features within the product.

Product Collaboration

• Work with product and engineering teams to translate client feedback into scalable product features.
• Prototype analytical workflows that may evolve into product capabilities.
• Contribute to product roadmap discussions based on client usage and market needs.

Stakeholder Communication

• Present insights and recommendations to internal and client stakeholders.
• Translate complex analytical outputs into clear business implications.
• Collaborate cross-functionally across product, engineering, and founders directly.

Qualifications

Education

• Bachelor’s or Master’s degree in Engineering, Computer Science, Data Science, Statistics, Economics, or a related quantitative field.

Experience

• 0–3 years of experience in  analytics, consulting, data science, or data engineering, specifically in the pharma industry .
• Experience working with  SQL and structured datasets .
• Basic programming skills in  Python or similar languages .
• Familiarity with  LLM tools, AI-assisted analysis, or prompt-based workflows  is preferred.

Domain Knowledge

• Exposure to  pharmaceutical or healthcare commercial data  (sales, claims, patient-level data, target lists etc.) is a prerequisite.
• Understanding of  commercial analytics, customer engagement, or market access workflows  is preferred.

Skills

• Strong analytical and problem-solving abilities.
• Ability to work in ambiguous, client-facing environments.
• Strong communication and storytelling with data.
• Comfort working across technical and business stakeholders.