Data Science / ML engineer - Manager
Posted Apr 17, 2026
As a Lead DS/ML Engineer at our company, you will play a crucial role in developing a cutting-edge reporting platform to measure and optimize online marketing campaigns. Your primary focus will be on building scalable data pipelines, developing ML models, and deploying solutions in production to support the reporting, insights, and recommendations platform. Here is a breakdown of your key responsibilities:
-
Data Engineering & Pipeline Development:
-
Design, build, and maintain scalable ELT pipelines for ingesting, transforming, and processing large-scale marketing campaign data. - Ensure high data quality, integrity, and governance using orchestration tools like Apache Airflow, Google Cloud Composer, or Prefect. - Optimize data storage, retrieval, and processing using BigQuery, Dataflow, and Spark for both batch and real-time workloads. - Implement data modeling and feature engineering for ML use cases. - Machine Learning Model Development & Validation:
-
Develop and validate predictive and prescriptive ML models to enhance marketing campaign measurement and optimization. - Experiment with different algorithms (regression, classification, clustering, reinforcement learning) to drive insights and recommendations. - Leverage NLP, time-series forecasting, and causal inference models to improve campaign attribution and performance analysis. - Optimize models for scalability, efficiency, and interpretability. - MLOps & Model Deployment:
-
Deploy and monitor ML models in production using tools such as Vertex AI, MLflow, Kubeflow, or TensorFlow Serving. - Implement CI/CD pipelines for ML models, ensuring seamless updates and retraining. - Develop real-time inference solutions and integrate ML models into BI dashboards and reporting platforms. - Cloud & Infrastructure Optimization: