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Strong brand, mid-level generalist ML role, metro hiring and broad skillset increase applicant competition.
Core ML and MLOps skills transfer across industries, though marketing analytics domain knowledge increases sensitivity.
Explicit 5+ years plus many mandatory ML, cloud, Databricks, and MLOps skills imply strict filters.
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Own advanced analytics and machine learning model development for marketing intelligence, personalization, and audience targeting across global digital channels.
Lead design and deployment of LLM and Generative AI use cases ensuring scalable and measurable business outcomes in Marketing Technology.
Partner cross-functionally to build scalable data science pipelines, maintain model quality, drive experimentation, and mentor junior data science team members.
Bachelor’s degree in a related field or suitable combination of education, experience, and training.
At least 5 years of experience in data science, machine learning, applied statistics, or advanced analytics.
Proficiency in Python, SQL, ML frameworks (scikit-learn, TensorFlow, PyTorch, XGBoost), and experience with cloud platforms (AWS, Azure, or GCP).
Experience with marketing/customer analytics domains including segmentation, personalization, churn prediction, CLV, attribution, media measurement, and audience targeting.
Experienced in deploying and maintaining ML models in production with strong knowledge of ML Ops, feature stores, and data engineering.
Demonstrated ability to lead AI-native practices, model governance, evaluation frameworks, and drive adoption of innovative data science techniques like Generative AI and LLMs.
Skilled at collaborating cross-functionally with engineering, product, analytics teams and mentoring data scientists within a global enterprise environment.