Forward Deployed Engineer - Product

Synthio LabsSan Francisco, CA

About The Position

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.

Requirements

  • Bachelor’s or Master’s degree in Engineering, Computer Science, Data Science, Statistics, Economics, or a related quantitative field.
  • 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.
  • Exposure to pharmaceutical or healthcare commercial data (sales, claims, patient-level data, target lists etc.) is a pre-requisite.
  • 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.

Nice To Haves

  • Familiarity with LLM tools, AI-assisted analysis, or prompt-based workflows is preferred.
  • Understanding of commercial analytics, forecasting, or market access workflows is preferred.

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.
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