Lead Data Scientist

Leadership and Team Management

• Lead, manage, and mentor a high-performing team of data scientists, ensuring excellence in technical execution and professional development.
• Define, implement, and refine the data science strategy and roadmap, aligning with the organization's long-term goals and evolving business needs.
• Cultivate a culture of technical innovation, collaboration, and continuous learning within the data science team.

Strategic Collaboration and Communication

• Partner with senior leadership to identify and address strategic opportunities and challenges through data science initiatives.
• Present complex, data-driven insights and strategic recommendations to executive stakeholders, driving high-level decision-making.
• Develop and nurture relationships with key stakeholders across the organization, ensuring effective collaboration and alignment on data-driven projects.

Innovation and Research

• Drive the exploration and adoption of Generative AI technologies, including large language models (LLMs), multimodal models, and foundation models, to develop innovative solutions for complex business problems.
• Drive the development and deployment of state-of-the-art data science methodologies, leveraging the latest advancements in machine learning, artificial intelligence, and computational techniques.
• Conduct pioneering research in emerging areas of data science, integrating new technologies and methodologies to solve complex business problems.
• Lead the evaluation and adoption of advanced tools, technologies, and frameworks to enhance the organization's data science capabilities.
• Design and implement GenAI-powered applications such as intelligent assistants, knowledge retrieval systems, automated analytics, and domain-specific copilots using modern AI architectures.

Project Management and Execution

• Oversee the execution of complex, high-impact data science projects, ensuring they meet rigorous technical standards, deadlines, and business objectives.
• Ensure the scalability, reliability, and robustness of data science solutions through advanced model development, deployment, and monitoring practices.
• Proactively manage project risks and mitigate potential issues, ensuring successful delivery and alignment with strategic goals.
• Lead the production deployment of Generative AI systems, ensuring responsible AI practices, model monitoring, cost optimization, prompt management, and scalable architecture.

Independent Contributor

• Independently design, develop, and implement sophisticated data science solutions for high-impact business problems, from conception through deployment.
• Solve critical and intricate data challenges with minimal supervision, demonstrating technical excellence and strategic insight.
• Identify and address gaps or opportunities for improvement in existing models, systems, and processes, driving continuous enhancement.
• Architect end-to-end GenAI pipelines, including prompt engineering, retrieval augmentation (RAG), fine-tuning strategies, and integration with enterprise data sources.

Thought Leadership and Continuous Learning

• Serve as a thought leader in the data science field, representing the organization at industry events, conferences, and forums with high-level presentations and publications.
• Promote a culture of continuous learning and technical excellence within the data science team and across the organization.
• Contribute to the organization's intellectual capital through research, white papers, and industry collaborations.

QUALIFICATIONS

• Ph.D., Master’s or Bachelor’s in Data Science, Computer Science, Statistics, Mathematics, or a related field.
• 10+ years of experience in data science or a related field, with a proven track record of leading and executing high-impact, technically complex projects.
• Extensive expertise in advanced machine learning algorithms, deep learning, statistical modeling, and AI, with hands-on experience in cutting-edge techniques.
• Mastery of programming languages such as Python, with extensive experience in advanced machine learning libraries and frameworks (e.g., TensorFlow, PyTorch, Keras).
• Advanced skills in SQL and hands-on experience with big data technologies.
• Demonstrated expertise in MLOps practices, including model deployment, monitoring, and optimization at scale.
• Exceptional problem-solving, analytical, and strategic thinking skills, with the ability to tackle the most complex data challenges.
• Proven leadership abilities, with experience managing and developing high-performing technical teams.
• Outstanding communication skills, both written and verbal, with the capability to convey complex technical concepts to diverse audiences and influence executive decision-making.
• Recognized as a thought leader in the data science community, with a strong portfolio of publications, conference presentations, or significant contributions to the field.
• Ability to manage and deliver multiple high-stakes projects simultaneously, with a deep understanding of how to align data science initiatives with overarching business objectives and strategies.
• Hands-on experience with Generative AI and Large Language Models (LLMs) including prompt engineering, fine-tuning, and evaluation.