Senior Data Scientist (AI ML)

As a Senior Data Scientist (AI/ML), you will be responsible for developing, validating, and deploying machine learning and generative AI solutions to optimize omnichannel communications for marketing and advertising. You will work closely with business stakeholders and engineering teams to translate use cases into scalable models, produce MLOps pipelines, and continuously monitor and improve model performance to drive measurable business impact. Key Responsibilities: - Partner with business stakeholders to identify, prioritize, and scope data science initiatives that deliver measurable marketing/advertising value, including GenAI-driven opportunities. - Design, build, validate, and productionize supervised and unsupervised ML models and generative AI solutions to optimize omnichannel communications and customer engagement. - Implement MLOps best practices: CI/CD for models, containerized deployments, monitoring, drift detection, and model refresh workflows. - Develop and maintain robust data pipelines, feature engineering processes, and model validation/testing frameworks. - Apply modern GenAI techniques (embeddings, RAG, prompt engineering) to create scalable, reliable solutions for content personalization, summarization, intent detection, or other use cases. - Perform exploratory data analysis, implement quality checks, and produce actionable insights and KPIs for stakeholders. - Collaborate with cross-functional teams (engineering, product, vendors/suppliers) to review modeling work, integrate models into platforms, and ensure operational readiness. - Monitor model performance post-deployment, iterate on models and thresholds, and document model lineage and assumptions. - Produce clear technical and non-technical documentation and present results to internal and external partners. Qualifications: - Advanced degree (Master's or PhD) in statistics, mathematics, economics, computer science, or a related quantitative field. - Proven track record applying ML/Deep Learning and demonstrable experience with generative AI/LLMs in business contexts. As a Senior Data Scientist (AI/ML), you will be responsible for developing, validating, and deploying machine learning and generative AI solutions to optimize omnichannel communications for marketing and advertising. You will work closely with business stakeholders and engineering teams to translate use cases into scalable models, produce MLOps pipelines, and continuously monitor and improve model performance to drive measurable business impact. Key Responsibilities: - Partner with business stakeholders to identify, prioritize, and scope data science initiatives that deliver measurable marketing/advertising value, including GenAI-driven opportunities. - Design, build, validate, and productionize supervised and unsupervised ML models and generative AI solutions to optimize omnichannel communications and customer engagement. - Implement MLOps best practices: CI/CD for models, containerized deployments, monitoring, drift detection, and model refresh workflows. - Develop and maintain robust data pipelines, feature engineering processes, and model validation/testing frameworks. - Apply modern GenAI techniques (embeddings, RAG, prompt engineering) to create scalable, reliable solutions for content personalization, summarization, intent detection, or other use cases. - Perform exploratory data analysis, implement quality checks, and produce actionable insights and KPIs for stakeholders. - Collaborate with cross-functional teams (engineering, product, vendors/suppliers) to review modeling work, integrate models into platforms, and ensure operational readiness. - Monitor model performance post-deployment, iterate on models and thresholds, and document model lineage and assumptions. - Produce clear technical and non-technical documentation and present results to internal and external partners. Qualifications: - Advanced degree (Master's or PhD) in statistics, mathematics, economics, computer science, or a related quantitative field. - Proven track record applying ML/Deep Learning and demonstrable experience with generative AI/LLMs in business contexts.