Forward Deployed Engineer - Data-as-a-Service

• Partner with the Sales Team on client discovery calls to provide technical depth, assess solution fit, and scope Data-as-a-Service opportunities
• Develop and present tailored technical assets including specifications, data dictionaries, sample datasets, and client-specific demonstrations to illustrate feasibility and value
• Define project scope and success criteria in collaboration with customer stakeholders and internal delivery teams, ensuring alignment on technical requirements and capacity
• Design and execute calibration processes including baseline batches, benchmark reports, and evaluation frameworks that establish measurable project success metrics
• Build and deploy evaluators, design and implement quality measurement systems to validate project outputs and ensure deliverables meet client expectations
• Generate synthetic datasets by developing or adapting existing pipelines to accelerate client engagements and augment training data
• Package and deliver production-grade datasets with standardized formatting, comprehensive documentation, and quality assurance
• Configure and build custom applications and off-platform solutions for non-standard or specialized client requirements
• Define production specifications and workflows, securing technical alignment with client teams to enable seamless go-live transitions
• Provide ongoing technical support to Delivery Managers, addressing complex questions, resolving technical blockers, and supporting customer rebuttals
• Maintain specification consistency and alignment across customer and internal teams throughout the engagement lifecycle
• Identify and document workflow best practices and automation opportunities, collaborating with DaaS Engineering to continuously improve delivery capabilities
• Maintain solution leaderboards and execute custom model benchmarking on existing datasets to demonstrate technical capabilities
• Drive continuous improvement of technical assets, evaluation frameworks, and delivery processes to enhance speed, quality, and scalability
• Support account growth by identifying upsell and cross-sell opportunities based on technical interactions with client engineering and research teams

• 2+ years of experience in data science and engineering roles
• Strong practical experience with Python, SQL, and data tooling (e.g., pandas, Plotly, Streamlit, Dash)
• Familiarity with LLM-based workflows and applying ML techniques in production contexts
• Experience leveraging Backend APIs and interpreting associated technical documentation

Equity in the form of employee stock options