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 life cycles, including validation, productionization, and optimization using frameworks such as Tensor Flow, 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, Sage Maker, or Azure ML.
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Ensure scalable, secure, and cost-efficient architectures with robust CI/CD pipelines in cloud environments.