What we're looking for

We are seeking a highly skilled Cloud Data Scientist to design, develop, and deploy the advanced machine learning models that fuel our data-driven decision-making. You will leverage your expertise in Google Cloud Platform, Python, SQL, and statistical modeling to create predictive and scalable AI solutions. Your work will directly impact the intelligence and capabilities of our products, empowering teams across the organization to extract valuable predictive insights.

What you'll do

Machine Learning &

- Model Development:

- Design, develop, and deploy scalable machine learning models using Google Cloud Platform services (Vertex AI, BigQuery ML, etc.).

- Implement efficient feature engineering processes from various data sources.

- Ensure model accuracy, fairness, and robustness throughout the lifecycle.

- Optimize model performance for inference speed and compute utilization.

Marketing Mix Modeling (MMM) &

- Advanced Analytics:

- Build, run, and maintain robust Marketing Mix Models (MMMs) to evaluate media channel performance and optimize marketing spend for clients.

- Implement and customize open-source MMM frameworks, such as Google Meridian or Meta Robyn, to align with client’s specific business requirements and datasets.

- Design and implement statistical experiments (A/B testing) for optimal product and feature evaluation.

- Collaborate with data engineers and marketing managers to understand their requirements and provide analytical solutions.

SQL &

- Feature Extraction:

- Write complex SQL queries and scripts to extract, explore, and analyze training data in BigQuery.

- Optimize analytical queries for performance and efficiency at scale.

Python &

- ML Frameworks:

- Develop custom Python applications to automate model training and deployment processes.

- Leverage Python libraries (e.g., scikit-learn, pandas, etc.)



for data modeling and analysis.

Model Monitoring and MLOps:

- Implement monitoring and alerting systems to proactively identify data drift and resolve model degradation.

- Investigate and troubleshoot model-related incidents in production.

Documentation:

- Maintain comprehensive documentation for all ML models, experimental results, and MLOps processes.

‍

What you'll need to bring

- Proven experience with Google Cloud Platform (GCP) and its AI/data services (Vertex AI, BigQuery).

- Solid SQL skills, with expertise in BigQuery SQL for large datasets.

- Proficiency in Python programming, with experience in machine learning and data science libraries.

- Experience in designing, training, and deploying statistical and machine learning models.

- Demonstrated comfort and hands-on experience running Marketing Mix Models (MMMs), specifically utilizing modern open-source frameworks like Meridian or Robyn.

- Proficiency in version control systems and collaborative Git-based development practices (e.g., branching strategies, pull requests, and code reviews).

Additional Skills:

- Strong problem-solving and analytical skills.

- Excellent communication and collaboration skills.

- Ability to learn new technologies and adapt to changing requirements.

‍

Nice to have

- Google Cloud Platform certification (e.g., Professional Machine Learning Engineer).

- Experience with MLOps and workflow orchestration tools (e.g., Kubeflow, Apache Airflow).

- Familiarity with data visualization tools (e.g., Looker).

- Practical skills and experience in Generative AI, including designing and building AI agents, working with Large Language Models (LLMs), or developing autonomous workflows.

Why Noise?

- Competitive salary and advantages package.

- Opportunities for professional development and growth.

- Work in a dynamic and innovative environment.

📌 Cloud Data Scientist (Vancouver)
🏢 Noise
📍 Vancouver