Data Science Lead - Generative AI

Role Overview: As a data-science leader, you will be responsible for transforming raw data into actionable insights and developing innovative AI products. You will manage projects from the initial framing of business questions to the deployment and monitoring of models in the cloud. You will also have the opportunity to introduce cutting-edge generative-AI concepts such as chat assistants and retrieval-augmented search. Leading a team of data professionals, you will collaborate closely with product, engineering, and business stakeholders to deliver measurable results. Key Responsibilities: - Designing and constructing predictive and forecasting models that drive tangible impact - Planning and executing A/B experiments to validate ideas and guide product decisions - Developing and maintaining data pipelines to ensure the integrity and timeliness of datasets - Spearheading generative-AI initiatives and implementing modern MLOps practices for model deployment and monitoring in the public cloud - Establishing robust monitoring and alerting mechanisms for accuracy, latency, drift, and cost Qualifications Required: - Strong foundation in statistics, experiment design, and end-to-end machine learning workflows - Proficiency in Python and SQL - Proven track record of transitioning models from notebooks to production environments - Hands-on experience with cloud platforms such as AWS, Azure, or GCP, including container-based deployment and CI/CD practices - Practical exposure to generative-AI projects, including prompt engineering, fine-tuning, and retrieval-augmented pipelines Additional Company Details: The company emphasizes upholding data governance and privacy standards across all projects in alignment with internal and industry guidelines. As a data-science leader, you will also play a crucial role in mentoring and coaching your team, conducting code reviews, and sharing best practices. Communicating complex findings in a clear and actionable manner to non-technical audiences will be a key aspect of the role. Continuous assessment of new tools and methodologies, including running proof of concepts to ensure solutions remain cutting-edge, is encouraged.,