Data Scientist
As a Data Scientist on this team, your mission is to turn raw data into a strategic asset. You will sit at the center of our marketing ecosystem, ensuring that every customer touchpoint is backed by high-quality, modeled data.
You aren't just building models; you are building the foundation they sit on. Using a modern stack based on GCP and dbt, you will create a unified "360-degree" view of our users. This role is a hybrid of deep analytical thinking and robust engineering, perfect for someone who believes that great insights are only possible with a world-class data architecture.
Requirements
- Modern Stack Mastery: Expert-level SQL skills and hands-on experience with dbt and Google Cloud Platform
- Engineering Standards: Comfortable with professional software workflows, including Git and CI/CD pipelines
- Analytical Mindset: A background in designing data models that are both scalable and easy for non-technical stakeholders to interpret
- Operational Ownership: You care about the stability of your systems and create the documentation and safeguards needed to prevent downtime
- Strategic Collaborator: Able to work alongside Product Managers and Analysts to turn business requirements into technical reality
- Tools: Experience integrating with enterprise CRMs (like HubSpot) is highly desirable
Responsibilities
- Pipeline Architecture: Design and maintain automated flows for internal and external marketing data. You will proactively manage data quality issues like schema changes or missing entries to keep our systems resilient
- Unified Customer Profiles: Partner with engineering teams to define and refine our "Customer 360" identity, ensuring all data products have clear ownership and high semantic integrity
- Advanced Data Modeling: Utilize dbt and BigQuery to transform raw event streams into sophisticated datasets for attribution, churn modeling, and audience segmentation
- Health & Reliability Monitoring: Develop custom observability tools to track data freshness and distribution, ensuring our marketing triggers always fire on accurate information
- Privacy-First Design: Implement data handling workflows that prioritize user consent and PII protection while maintaining operational efficiency
Data Scientist
What will be your next steps?
Quick non-technical conversation
Our initial conversation is a brief, non-technical discussion to understand your background and career aspirations. We're keen to learn about your communication style and how you approach teamwork and decision-making.
60 to 90 minutes technical interview
This in-depth technical assessment, lasting 60 to 90 minutes, is designed to evaluate your specific skills and expertise. We will present you with challenges relevant to our client's requirements.
Client interview
In this stage, you will meet directly with the client for a final technical discussion. This interview will be similar in format to our internal technical assessment, allowing the client to see firsthand how your expertise aligns with their specific project needs and team.
Offer
Congratulations on successfully completing our rigorous evaluation process. We are pleased to extend an offer and recommend you to our clients.