À propos
Looking for a Senior Data Scientist & Machine Learning Engineer to bridge the gap between advanced AI engineering and strategic business insights. Need to take ownership of the entire ML lifecycle—from critical data analysis to architecting production-grade, GCP-based ML pipelines and advanced analytics systems. Translate ambiguous business problems into scalable, production-grade AI solutions, drive technical excellence, and mentor team members in engineering best practices. Roles & Responsibilities
Technical Ownership & MLOps: End-to-end responsibility for designing, deploying, and monitoring scalable ML pipelines and AI solutions. You design from scratch, or convert experimental notebooks, into robust, production-ready code with automated CI/CD and feature management. Critical Analysis & Strategy: Autonomously dive into complex datasets to uncover growth opportunities, validate model assumptions, and deliver executive-level insights on business metrics, forecasting, and user behavior. Data Engineering & Collaboration: Act as a bridge to Data Engineering teams to co-design robust data architecture. You possess strong foundational skills in building optimized data pipelines, modeling clean schemas, and ensuring high-quality data ingestion for downstream ML models. Senior Leadership: Act as a strategic partner to product and business stakeholders, manage project delivery timelines, and champion rigorous code quality and best practices across the team. Preferred Domain Expertise: Strong preferred experience in Marketing Science, specifically around building and calibrating Marketing Mix Models (MMMs) and attribution frameworks to optimize ROI and budget allocation. Tools and Technologies
Google Cloud Platform (GCP)
Data & Analytics: BigQuery (Advanced SQL, BigQuery ML), Cloud Storage AI & MLOps: Vertex AI (Pipelines, Model Registry, Feature Store), Agent Builders / Agent Platforms, Kubeflow
Languages & Core Data Science
Programming: Python (Expert), SQL (Advanced) Libraries: Scikit-Learn, XGBoost, LightGBM, TensorFlow, or PyTorch
Preferred Marketing Science & Bayesian Modeling
MMM Frameworks: Meridian, LightweightMMM Probabilistic Programming: PyMC, Stan, or similar Bayesian libraries
Engineering & CI/CD
DevOps:
Compétences linguistiques
- English
Avis aux utilisateurs
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