Were looking for a Data Scientist, Applied Intelligence to join our Intelligence group within the broader Product and Engineering organization.
This is not a traditional analytics role. You will help design the logic, data structures, and evaluation systems that allow intelligence to operate inside a creative production environment. That includes representing workflows in structured ways, reasoning about change and dependencies, tracking provenance and version history, and building systems that support explainable, human-guided decision-making.
Youll work closely with engineering, product, and creative stakeholders to turn ambiguous workflow problems into reliable, measurable, and useful systems.
What Youll Do- Contribute to the design and build intelligence systems that help Liquid Engine understand workflow context, track change over time, and support consistent outputs
- Translate creative and production workflows into structured representations such as entities, relationships, rules, and graphs
- Help develop systems for tracking state, version history, provenance, and dependencies across workflows
- Build rule-based and heuristic systems that identify conflicts, evaluate consistency, and surface issues before they create downstream problems
- Support change impact analysis by helping the system reason about dependencies, cascades, and workflow consequences
- Develop evaluation frameworks that measure system usefulness, output quality, and reduction of manual rework
- Partner with engineering on event pipelines, data models, and system architecture that support intelligent system behavior
- Contribute to explainable recommendation and decision-support systems grounded in workflow context
- Help define telemetry, measurement, and governance approaches for intelligence features across the platform
What Were Looking ForCore Skills
- 4-8+ years in data science, applied ML, or systems-oriented analytics
- Strong Python and SQL proficiency
- Experience working with complex data systems
- Familiarity with graph-based or relational reasoning
- Understanding of deterministic vs probabilistic systems
- Ability to translate ambiguous domains into structured approaches
- Strong communication skills across technical and non-technical teams
Nice to Have
- Experience with generative AI systems or media pipelines
- Exposure to knowledge graphs or dependency systems
- Experience with experimentation or telemetry systems
- Familiarity with governance, audit, or compliance systems
- Experience building internal tools or operator-facing systems
How You Work- You think in systems, not just models
- You value clarity, explainability, and correctness
- You are comfortable operating in ambiguity
- You avoid premature abstraction or unnecessary complexity
- You collaborate closely with engineers, product, and creative teams
- You know when restraint is the right solution
