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OverviewWe re seeking a visionary data scientist to lead the evolution of AI-driven recommendation systems and monetization strategies. This role combines technical leadership, strategic thinking, and hands-on expertise in machine learning and generative AI to deliver transformative solutions at scale.
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Key Responsibilities- Architect and implement advanced machine learning systems that power intelligent recommendations and personalized experiences.
- Define and execute a forward-looking technical vision for AI capabilities, including generative AI and agent-based systems.
- Collaborate with engineering, product, and analytics teams to align technical strategy with business objectives.
- Design and optimize large-scale AI platforms, ensuring scalability, reliability, and operational excellence.
- Stay ahead of emerging trends in AI, identifying opportunities and risks to guide innovation and maintain competitive advantage.
- Mentor and guide data scientists and engineers, fostering best practices and technical excellence.
- Communicate complex technical concepts clearly to both technical and non-technical stakeholders.
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Required Qualifications- MS or PhD in Computer Science, Machine Learning, Data Science, or related field.
- 10+ years of experience in data science, software engineering, or AI systems architecture.
- Proven track record of building and scaling machine learning systems for real-world applications.
- Strong programming skills in Python, Java, or C++.
- Expertise in designing next-generation AI solutions, including generative AI and semantic search.
- Exceptional communication and leadership skills, with the ability to influence cross-functional teams.
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Preferred Qualifications- Experience in ad technology or monetization strategies.
- Background in developing generative AI capabilities and supporting infrastructure.
- Ability to thrive in fast-paced, large-scale environments.
data scientist, machine learning, AI, generative AI, recommendation systems, semantic search, knowledge graph, Python, Java, C++, big data, ETL, ad tech, monetization, data architecture, AI systems, ML pipelines, predictive modeling, deep learning, cloud computing, distributed systems, operational excellence, leadership, mentoring, innovation
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