Marketing Data Science Manager

We are seeking a skilled and versatile Data Science Manager with AI familiarity to join our growing team. In this role, you’ll collaborate with practice leaders, engineers, and cross-functional stakeholders to solve complex business challenges using data science and AI-driven approaches. You’ll work on end-to-end data science initiatives, with opportunities to design and implement cutting-edge generative AI (GenAI) and LLM-powered solutions. Key Responsibilities Data Science & Analytics • Partner with practice leaders and clients to understand business problems, industry context, data sources, risks, and constraints. • Translate business needs into actionable data science solutions, evaluating multiple approaches and clearly communicating trade-offs. • Collaborate with stakeholders to align on methodology, deliverables, and project roadmaps. • Leverage Machine Learning and Data Analysis to optimize marketing campaigns • Conduct A/B tests to improve campaign performance measure campaign effectiveness, and increase engagement and conversion rates.  AI & Generative AI Collaboration In addition to traditional data science responsibilities, you will collaborate with AI and engineering teams to: • Design and implement production-grade AI solutions leveraging LLMs, transformers, retrieval-augmented generation (RAG), agentic workflows, and generative AI agents. • Optimize prompt design, workflows, and pipelines for performance, accuracy, and cost-efficiency. • Build multi-step, stateful agentic systems that utilize external APIs/tools and support robust reasoning. • Deploy GenAI models and pipelines in production (API, batch, or streaming) with a focus on scalability and reliability. • Develop evaluation frameworks to monitor grounding, factuality, latency, and cost. • Implement safety and reliability measures such as prompt-injection protection, content moderation, loop prevention, and tool-call limits. • Work closely with Product, Engineering, and ML Ops to deliver robust, high-quality AI capabilities end-to-end. •   • Develop and manage detailed project plans including milestones, risks, owners, and contingency plans. • Create and maintain efficient data pipelines using SQL, Spark, and cloud-based big data technologies within client architectures. • Collect, clean, and integrate large datasets from internal and external sources to support functional business requirements. • Build analytics tools that deliver insights across domains such as customer acquisition, operations, and performance metrics. • Perform exploratory data analysis, data mining, and statistical modeling to uncover insights and inform strategic decisions. • Train, validate, and tune predictive models using modern machine learning techniques and tools. • Document model results in a clear, client-ready format and support model deployment within client environments. Required Skills & Experience • 5+ years of hands-on experience in Data Science, including model building and ML Ops • Experience in email marketing and direct marketing  • Experience managing people • Proficiency in Python , SQL , and tools like Pandas , Scikit-learn , NLTK / spaCy , and Spark • Familiarity with digital marketing ecosystem (e.g., clickstream analytics) and recommendation systems  • Experience deploying models via APIs  or integrating them into batch processing pipelines • Working knowledge of cloud data platforms  (e.g., AWS S3, Redshift, GCP, Azure) • Ability to manage data pipelines and ETL processes with a solid understanding of data engineering best practices • Strong communication and collaboration skills, including experience engaging directly with clients Preferred Qualifications • Exposure to ML Ops tools such as MLflow , Kubeflow , or SageMaker • Expe