The Role
Partner with clients and product teams to deploy data-driven analytics and AI features for pharma commercial use cases. Build and optimize SQL-driven analyses, design LLM-enabled workflows, translate business questions into data models, prototype product capabilities, and present insights to stakeholders.
Summary Generated by Built In
We’re building the next generation of conversational voice and video AI for life sciences—intelligent with 100% regulatory compliance. Our AI medical experts help pharma teams engage doctors, support patients, and unlock insights faster than ever before. We’ve just raised our seed, signed our first customers, and are scaling fast. If you're excited about building real-world AI in an early stage startup and shape not just our product, but our identity and culture —this is your moment.
We move like owners. Everyone at SynthioLabs has the autonomy and the responsibility to drive projects, challenge decisions, and push things forward. We don’t wait for permission. If you see a gap, you fill it. If you see a better way, you try it.
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.
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.
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.
Skills Required
- Bachelor's or Master's degree in Engineering, Computer Science, Data Science, Statistics, Economics, or related quantitative field
- 0-3 years experience in analytics, consulting, data science, or data engineering in the pharma industry
- Experience writing and optimizing SQL queries against structured datasets
- Basic programming skills in Python, R, or similar languages
- Exposure to pharmaceutical or healthcare commercial data (sales, claims, patient-level data, target lists)
- Familiarity with LLM tools, AI-assisted analysis, or prompt-based workflows
- Understanding of commercial analytics, forecasting, or market access workflows
- Strong analytical problem-solving, communication, and ability to work in client-facing ambiguous environments
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The Company
What We Do
Synthio Labs is an AI-driven technology company that provides an agentic AI platform for pharmaceutical and life sciences teams. Their platform enables compliant, conversational AI interactions with healthcare professionals and patients, automating medical information requests, clinical guideline education, and field team support to improve engagement and adherence in the pharmaceutical industry.
