Lead Data Scientist

Key Responsibilities

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 development and deployment of state-of-the-art data science methodologies, leveraging the latest advancements in machine learning, artificial intelligence, LLMs, 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. 

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. 

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, LLM, 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/LLMOps 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.