Forward Deployed Engineer - Product

SynthioLabs Ltd

  • San Francisco, CA
  • 14 days ago

    Highlights

    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. 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.

    Numbers & Facts

    LocationSan Francisco, CA

    Description

    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.

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