Data Scientist, Applied Intelligence

secret-level; Los Angeles (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

secret-level seeks a seasoned data scientist to design and build intelligence systems that understand workflow context, track changes, and support consistent outputs.

You will translate workflows into structured representations, track provenance, and develop graph-based reasoning. You’ll collaborate with engineers to shape data models and governance, aiming for explainable recommendations across the platform.

Qualifications

• 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.

Responsibilities

• Contribute to the design and build intelligence systems that help understand workflow context, track change over time, and support 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.

Skills

Data science / applied ML

Python

SQL

Complex data systems

Graph-based reasoning

Deterministic vs probabilistic

Structured problem solving

Communication

Job description

What You’ll 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 We’re Looking For

Core 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