We are seeking an experienced and innovative Lead AI Architect with experience in the AWS stack to join our dynamic team. In this role, you will work closely with stakeholders to harness the power of data and drive business insights through advanced statistical models and machine learning algorithms. As the technical leader of our AI teams, you will provide mentorship and guidance while ensuring effective communication of complex data insights to non-technical stakeholders

Stakeholder Collaboration: Engage with stakeholders to understand the underlying data and explore potential use cases, ensuring alignment with business goals and objectives.

Advanced Model Development: Design and implement sophisticated statistical models and machine learning algorithms to drive business insights and develop innovative solutions.

Team Leadership and Mentorship: Lead and mentor the data science team, providing technical guidance, fostering professional development, and ensuring the successful execution of projects.

Effective Communication: Communicate complex data insights in a clear, concise, and actionable manner to non-technical stakeholders, ensuring informed decision-making and strategic planning.

Project Management: Oversee data science projects from conception to completion, ensuring timely delivery, adherence to quality standards, and alignment with business objectives.

Data Strategy and Vision: Develop and execute a strategic vision for data science within the organization, identifying opportunities to leverage data for competitive advantage.

Cross-functional Collaboration: Collaborate with cross-functional teams, including product managers, engineers, and business analysts, to integrate data-driven insights into business processes and product development.

Innovation and Research: Stay abreast of the latest advancements in data science, machine learning, and AI, driving innovation and incorporating cutting-edge techniques into the team s work.

Performance Monitoring and Optimization: Monitor the performance of deployed models and algorithms, making necessary adjustments and optimizations to ensure continued accuracy and effectiveness.

Technical Documentation: Create and maintain comprehensive documentation for models, algorithms, and processes, ensuring transparency and reproducibility of results.

Ethical Data Practices: Promote and ensure adherence to ethical data practices, including data privacy, security, and compliance with relevant regulations and standards.

Expertise in statistical analysis, data science, machine learning, and statistical analysis.

Strong programming skills in Python, R, or similar languages.

Experience with data visualization tools ideally AWS QuickSight or similar tools like Tableau, Power BI etc.

Experience architecting Data Warehousing solutions and Data Pipelines for Machine Learning algorithms with AWS technologies (Amazon Redshift, AWS Glue, EMR etc.)

Experience in applying machine learning algorithms to achieve business outcomes.

Experience architecting recommendation solutions a plus

Excellent communication and stakeholder management skills.

Ideally PhD or Master's degree in Computer Science, Statistics, Mathematics, or related field or BSc with professional certifications.

Machine Learning and Data Science / Python / Pandas / NumPy / Sci-kit learn /TensorFlow /PyTorch / AWS Lambda / AWS Glue / AWS Redshift / AWS Athena / AWS QuickSight