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.
— Sarah J.
·
Marketing Manager
★★★★★
Verified
