Overview

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.

Responsibilities

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, R, 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 pre-requisite.
Understanding of commercial analytics, forecasting, 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.

What Makes This Role Unique

Work directly with clients to shape how a product is used in real-world environments.
Blend consulting-style analytics with product development.
Apply modern AI and LLM tools to commercial data problems.
Help build the next generation of AI-driven analytics platforms for life sciences.