Primary Skill /s - Machine Learning to Customer Marketing initiatives -Python and libraries like PySpark, TensorFlow, PyTorch, and Scikit-learn big data ecosystems (e.g., Hadoop/Spark) and cloud platforms (e.g., Azure, AWS, GCP)
Required Skills & Qualifications
• Strong programming skills in Python with proven experience building production-grade ML systems.
• Hands-on expertise in PySpark and distributed data processing for feature engineering and model training.
• Practical experience with ML frameworks such as Scikit-learn, and at least one deep learning framework (TensorFlow or PyTorch).
• Solid understanding of supervised/unsupervised ML techniques and evaluation metrics (AUC, F1, precision/recall, lift, calibration).
• Experience working within big data ecosystems (Hadoop, Spark) and data lake/lakehouse concepts.
• Cloud experience in one or more platforms: Azure / AWS / GCP (compute, storage, orchestration, security basics).
• Familiarity with MLOps practices: model versioning, reproducibility, CI/CD, automated testing, and monitoring.
• Strong communication skills and ability to explain model outputs to business partners (especially marketing stakeholders).
Preferred / Nice-to-Have
• Experience with customer marketing analytics: segmentation, personalization, recommender systems, attribution, uplift modeling, MMM, or experimentation.
• Knowledge of feature stores, ML pipeline orchestration (Airflow, ADF, Step Functions, Composer), and model registries.
• Experience with containerization & orchestration: Docker/Kubernetes.
• Exposure to modern data platforms: Databricks, Snowflake, BigQuery, SageMaker, Vertex AI, Azure ML.
• Familiarity with data governance, PII handling, consent frameworks, and regulatory requirements (industry dependent
