Head of Data, AI

Burq

Head of Data & AI at Burq leading the data and ML team while building the intelligence platform. Overseeing data governance, ML systems, and partnering with cross-functional leaders.

Posted 7/15/2026full-timeRemote • 🇺🇸 United StatesLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in managing and optimizing data platforms, including modern data warehouse design and machine learning systems. Proven ability to lead teams while driving data-driven decision-making and product development.

Highest-signal resume keywords

Data Platform ManagementMachine Learning Model DevelopmentModern Data Warehouse DesignStakeholder ManagementTeam Leadership

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data GovernanceData IngestionFeature PipelinesForecastingOptimizationMLOpsPerformance OptimizationModel EvaluationSemantic Layer DesignBusiness Analytics

Soft Skills

Team LeadershipStakeholder ManagementCommunicationDecision-MakingProblem-Solving

Tools & Technologies

SnowflakeBigQueryDbtMachine Learning SystemsAI/LLM Technologies

Industry Keywords

Data-Driven Decision MakingHigh-Growth StartupData ProductsAnalytics EngineeringData Science

Tech Stack

Tools & technologies

BigQuery

About the role

Key responsibilities & impact

Own the full data platform — the warehouse, streaming and batch ingestion, the semantic layer, and BI infrastructure.
Define and enforce data governance — access management, quality standards, and a well-modeled, trustworthy "gold" layer.
Make the warehouse the source of truth for operational, product, and financial analytics.
Build the models that power delivery intelligence — forecasting, prediction, optimization, matching/allocation, and reliability scoring that turn our data into better real-time decisions.
Stand up the ML systems that make this real and reliable: feature pipelines, training, serving, evaluation, and drift monitoring.
Design the learning loop — instrument decisions and outcomes so models continuously improve.
Drive the AI agent initiative to production, partnering with product and engineering on the surrounding workflows.
Manage and grow the data and ML team (starting from a small core) — hire data engineers, analytics engineers, and data scientists/ML engineers as the platform matures.
Establish a clear intake process for ad hoc data requests so the team works from a roadmap, not in reactive mode.
Partner with Sales, Customer Success, and Finance on data-driven analyses and decisions.

Requirements

What you’ll need

8+ years in data/ML, including 2+ years in a leadership or staff-level role owning a data or ML platform.
Player-coach — you lead a team and still go deep in the technical work: architecture, modeling, and code review.
Strong on both halves of the role:
- Data platform — modern data warehouse design (e.g., Snowflake/BigQuery), streaming + batch ingestion, dbt or equivalent, performance and cost optimization, governance.
- Machine learning — you've built and shipped production models (forecasting, optimization, ranking/matching, or prediction) with real business impact, plus the ML systems around them (feature pipelines, serving, monitoring/MLOps).
Experience building data and ML products, not just pipelines — you understand how data and models serve product and business goals.
Familiarity with modern AI/LLM and agentic data work is a strong plus.
Strong stakeholder management — you can say no to an ad hoc request with a good reason and a better alternative.
Experience at a high-growth startup or scale-up where the platform was built, not inherited.

Benefits

Comp & perks

Competitive salary, stock options, and performance-based bonuses
Fully remote
Comprehensive medical, vision, and dental insurance