Lead Data Scientist

As a Lead Data Scientist, you will play a pivotal role in leading the development and deployment of advanced machine learning models and generative AI solutions for our clients. You will be responsible for designing, implementing, and optimizing data science projects from inception to deployment, using state-of-the-art cloud-native technologies on AWS and GCP. This role requires a strong focus on MLOps, ensuring efficient model lifecycle management and integration into business processes.

Key Responsibilities:

Lead and Manage Data Science Projects: Oversee the end-to-end lifecycle of data science projects, from data preprocessing, model development, model deployment and monitoring on the cloud

Develop Machine Learning Models: Design, build, and deploy complex machine learning models and generative AI solutions that address client-specific business challenges.

Implement MLOps Practices: Establish robust MLOps pipelines and frameworks to automate, monitor, and optimize model deployment, retraining, and scalability using cloud-native tools and platforms.

Collaborate with Cross-functional Teams: Work closely with data engineers, software developers, and domain experts to ensure seamless integration of data science solutions within the client s ecosystem.

Client Engagement: Act as a subject matter expert in client meetings, presentations, and workshops, providing insights and recommendations on machine learning and AI strategies.

Stay Current with Industry Trends: Continuously monitor advancements in machine learning, generative AI, and cloud technologies, incorporating relevant innovations into projects.

Mentor and Develop Talent: Provide technical leadership and mentorship to junior data scientists and team members, fostering a culture of continuous learning and innovation.

Technical Expertise:

Proven experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-Learn) and generative AI models (e.g., GPT, DALL-E, diffusion models).

Strong proficiency in Python and rele