What are the responsibilities and job description for the Forward Deployed Data Scientist position at Growth Signals?
Forward Deployed Data ScientistLocation: Boston, MA preferred, remote may be consideredType: Full-timeStage: Seed-stage AI StartupIndustry: B2B SaaS / Artificial Intelligence
As a Forward Deployed Data Scientist (FDDS) at Growth Signals, you'll work directly with enterprise customers to help them get real value from our GenAI platform. You'll be their primary technical partner, combining data science expertise with product knowledge and customer success to solve their toughest challenges.
In this role, you'll translate business problems into practical solutions—building custom agentic workflows on our platform that help enterprises make better strategic decisions powered by AI.
Key ResponsibilitiesWork directly with customers:
- Partner with executives and operational teams to understand their business challenges and identify where our GenAI platform can have the biggest impact
- Act as the technical expert on our platform, translating business needs into agentic workflows and custom solutions
Build and implement solutions:
- Integrate customer data sources and APIs into our platform's research agents and AI workspace
- Design and deploy custom LLM workflows and agents for analyzing complex customer data
- Develop and automate data science workflows tailored to each customer's needs
- Own the full implementation—from initial discovery through deployment and adoption
Technical skills:
- Master's degree with 3 years of experience (including 1 year client-facing) or Bachelor's degree with 6 years of experience in data science, ML engineering, or technical consulting. SaaS experience is a plus.
- Strong data engineering skills (ETL, pipelines, cloud data warehousing) combined with data science fundamentals (modeling, statistics)
- Hands-on experience with LLMs—building solutions, prompt engineering, and working with GenAI frameworks
- Proficiency in Python and NoSQL databases (MongoDB)
- Experience with statistical modeling, machine learning, and model evaluation
- Familiarity with cloud platforms (Azure, AWS, or GCP) and production deployment practices
Working style:
- Experience working with both technical and non-technical stakeholders
- Comfortable in an early-stage startup environment—you're self-directed and thrive with ambiguity
- Willing to travel up to 50% for on-site customer work
- Able to communicate technical concepts clearly to business audiences