DVP - Data Science AI

AI & Machine Learning

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Design, develop, and implement machine learning models for predictive analytics, natural language processing (NLP), computer vision, or recommendation systems.

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Lead end-to-end AI project lifecycles, including validation, productionization, and optimization using frameworks such as TensorFlow, PyTorch, and scikit-learn.

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Stay updated with the latest advancements in Generative AI and foundation models, evaluating and integrating them as needed.

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Partner with cross-functional teams to identify AI use cases and deliver measurable business value.

Data Science & Analytics

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Lead the end-to-end analytics lifecycle, from data exploration to actionable insights and product development.

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Collaborate with data engineers and analysts to build impactful solutions that drive business outcomes.

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Leadership & Strategy

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Mentor and guide junior team members, fostering their professional growth.

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Contribute to the enterprise AI and cloud strategy, including roadmap planning and vision setting.

Cloud Architecture & Engineering

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Architect and design cloud-native AI and data platforms on GCP (preferred), AWS, or Azure.

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Optimize data pipelines and machine learning workflows using services like Vertex AI, SageMaker, or Azure ML.

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Ensure scalable, secure, and cost-efficient architectures with robust CI/CD pipelines in cloud environments.