Sohaib

Head of Data and AI

Hubcom • Fulltime

Aug 2024 - Present • 2 yrs 2 mos

- Lead the strategic direction of data and AI initiatives, ensuring alignment with overall business goals and driving digital transformation across the organization. - Develop and execute data governance frameworks to ensure high data quality, security, and compliance with industry regulations and standards. - Spearhead AI innovation, overseeing the development of advanced analytics, machine learning, and AI-driven solutions that deliver actionable insights and business value. - Drive data-driven decision-making, empowering cross-functional teams with the necessary tools, analytics, and insights to improve operational efficiency and customer experiences. - Collaborate with executive leadership to identify opportunities for leveraging data and AI to enhance product offerings, improve customer experiences, and create competitive advantages. - Build and lead high-performing teams, fostering a culture of innovation, continuous learning, and cross-disciplinary collaboration between data scientists, engineers, and business units. - Ensure scalability and reliability of data platforms and AI solutions by managing infrastructure, cloud solutions, and emerging technologies to meet evolving business needs. - Monitor AI ethics and data privacy concerns, ensuring responsible and ethical AI practices while addressing regulatory and societal impacts of AI deployment. - Establish key performance metrics to measure the impact of data and AI initiatives on business outcomes, continuously optimizing for better performance and innovation. - Lead the digital transformation journey, guiding the organization in embracing data-first and AI-powered mindsets across departments to foster innovation and growth.

Senior Data Scientist / AI Practice Lead

Royal Cyber Inc • Fulltime

Nov 2023 - Oct 2024 • 11 mos

- Spearheading advanced Research & Development in Generative AI, leveraging cutting-edge techniques to create Innovative Solutions and Applications - Driving projects focused on Large Language Models (LLMs) to extract Insights & Patterns from vast Datasets - Contributing to Enhanced Decision-Making and Problem-Solving Capabilities - Applying Expertise in Data Science methodologies to Design, Implement, & Optimize Algorithms that uncover hidden Trends and drive Actionable Insights - Collaborating with cross-functional teams to Develop and Deploy Machine Learning Models, Ensuring Alignment with Business Objectives & Industry Best Practices - Contributing to the Development and Enhancement of Data-Driven products by harnessing the power of ARTIFICIAL INTELLIGENCE and Statistical Modeling - Employing deep expertise in Machine Learning frameworks and tools to build Scalable, Efficient, and High-Performance Models - Championing Continuous Learning and Knowledge Sharing within the Organization by Mentoring and guiding Junior Data Scientists and Team Members - Evaluating Model Performance, iterating on Strategies, and Fine-Tuning Algorithms to achieve Optimal results in Complex, Real-World Scenarios

Lead Instructor & Consultant

Dice Analytics • Parttime

Mar 2023 - Oct 2024 • 1 yr 7 mos

- Conduct Comprehensive DevOps and MLOps & Generative AI Training Sessions for Professionals and Teams - Covering Essential Methodologies, Tools, and Best Practices for DevOps, MLOps & Generative AI - Design and Deliver tailored Curriculum addressing the Intersection of Development, Operations, & Machine Learning - Provide hands-on instruction in: -> Deploying and Managing Infrastructure -> CI/CD Pipelines (GitHub Actions, GitLab Ci/CD, Jenkins) -> Version Control (Git, GitHub, GitLab, BitBucket) -> Automated Testing within DevOps/MLOps Environments (MLflow) - Offer expertise in Cloud Platforms (AWS, Azure, GCP) and Containerization Technologies (Docker, Kubernetes) to Optimize Machine Learning Workflows - Guide participants through the Integration of Machine Learning Models into Production Systems, emphasizing Scalability, Reliability, & Efficiency - Collaborate with Industry Experts to Develop up-to-date Training Materials, Ensuring Alignment with the Latest Advancements and Trends in DevOps & MLOps - Deploying Applications/Microservices on Amazon Web Services (AWS) platforms via different Services including -> AWS EC2 -> AWS ECR -> AWS ECS (EC2 & Fargate) -> AWS LAMBDA -> AWS RDS -> AWS S3 -> AWS Light Sail -> AWS Load Balancer -> AWS VPC & Security Groups -> AWS IAM - Foster an Interactive Learning Environment by Facilitating Discussions, Workshops, and Practical Exercises that Reinforce Theoretical Concepts with Real-World Applications - Support Professional Growth by Mentoring Individuals and Teams, Equipping them with the Skills needed to Navigate Complex DevOps and MLOps Landscapes Effectively - Evaluate Learning Outcomes & Provide Constructive Feedback, Enabling Participants to Continually Enhance their Proficiency in Leveraging DevOps & MLOps Principles