Jobs at Life Science Connect (Now Hiring) — 5 open

About Us

Why This Role Matters

What You'll Actually Do

• Translate Strategy into Engineering Execution: Partner with Product Leadership and Engineering to transform strategic initiatives into clear technical requirements, user stories, workflows, APIs, and acceptance criteria that engineers can immediately build from.
• Drive AI-Augmented Analysis: Use modern AI tools to rapidly produce requirements, process models, technical documentation, and data mappings while maintaining exceptional structural accuracy and logical consistency.
• Design Intelligent Product Workflows: Analyze complex business processes and design scalable workflows that leverage identity, personalization, analytics, AI services, and customer intelligence across our product ecosystem.
• Own Product Specifications: Produce implementation-ready documentation including PRDs, functional specifications, user stories with rigorous acceptance criteria, API contracts, process flows, and data mappings.
• Partner Deeply with Engineering: Work directly alongside Full Stack Engineers to clarify requirements, answer implementation questions, refine technical solutions, and remove ambiguity before development begins.
• Enable Data Intelligence: Collaborate with Data Engineering to define modern data models, ingestion patterns, warehouse requirements, reporting needs, and customer intelligence workflows while ensuring data quality throughout the product lifecycle.
• Validate What We Build: Support testing, feature validation, and release readiness by ensuring delivered functionality aligns perfectly with business objectives and technical specifications.
• Improve How We Work: Continuously improve documentation standards, Agile practices, AI-enabled delivery workflows, and product discovery processes to help the entire engineering organization move faster with greater confidence.

What We're Looking For

5+ Years of Business Analysis Experience

Technical Fluency

• REST APIs and JSON payload structures
• Headless CMS architectures and decoupled front-ends
• Identity, Authentication, and Customer Identity frameworks (CIAM)
• Relational and modern cloud data models (Snowflake)
• Event Tracking, telemetry, and Customer Journey Analytics
• Cloud-based application architectures and system integrations

AI-Augmented Analyst

Core Traits

• Product Mindset: You naturally ask "why" before "what." You understand that every requirement should tie directly to customer value, operational efficiency, measurable business outcomes, or revenue growth.
• Systems Thinker: You enjoy untangling complex processes, identifying hidden technical dependencies, simplifying workflows, and designing scalable architectural solutions.
• Excellent Communicator: You can confidently facilitate alignment between executives, business stakeholders, designers, engineers, and data teams while effortlessly adapting your communication style to your audience.
• Highly Autonomous: You excel in distributed teams where asynchronous documentation, radical ownership, proactive communication, and independent problem-solving are essential.

Preferred Experience

• Agile/Scrum product development in highly iterative environments
• Technical Business Analysis within cloud-native software engineering organizations
• Headless CMS platforms (Optimizely preferred)
• Snowflake or modern cloud-native data platforms
• Customer Identity and Access Management (CIAM) systems
• Product analytics, event streaming, and customer journey mapping
• API integration, contract design, and webhook architecture
• AI-assisted software delivery tools and prompts
• Jira, Confluence, and structured ticket workflows
• Lucidchart, Miro, or similar visual modeling tools

Success in Your First 90 Days

• Built trusted, seamless relationships across Product, Engineering, Data, and DevOps.
• Produced implementation-ready specifications that measurably reduce engineering clarification and rework cycles.
• Accelerated delivery velocity through high-fidelity, AI-assisted documentation and rapid analysis workflows.
• Elevated the quality and consistency of product requirements, downstream testing logic, and acceptance criteria.
• Contributed directly to launching customer-facing features with clear, trackable business impact.
• Established repeatable documentation, mapping, and analysis practices that scale natively with our engineering organization.