Full-Time Lead Data Scientist

Lead Data Scientist

Lead the development and deployment of advanced machine learning models and generative AI solutions for clients. Design, implement, and optimize data science projects from inception to deployment using cloud-native technologies on AWS and GCP. Focus on MLOps for efficient model lifecycle management and business process integration.

1. Lead and Manage Data Science Projects: Oversee the entire data science project lifecycle (data preprocessing, model development, deployment, and monitoring on the cloud).
2. Develop Machine Learning Models: Design, build, and deploy complex machine learning models and generative AI solutions addressing client needs.
3. Implement MLOps Practices: Establish robust MLOps pipelines and frameworks automating model deployment, retraining, and scaling using cloud-native tools.
4. Collaborate with Cross-functional Teams: Work with data engineers, software developers, and domain experts to ensure seamless integration.
5. Client Engagement: Act as a subject matter expert in client meetings, providing insights and recommendations.
6. Stay Current with Industry Trends: Monitor advancements in machine learning, generative AI, and cloud technologies, incorporating innovations into projects.
7. Mentor and Develop Talent: Provide technical leadership and mentorship to junior team members.

Technical Expertise:

• Proven experience with machine learning frameworks (TensorFlow, PyTorch, Scikit-Learn) and generative AI models (GPT, DALL-E).
• Strong proficiency in Python and relevant data science libraries (NumPy, Pandas, SciPy).
• Experience with ML frameworks on the cloud (GCP Vertex AI, Vertex AI pipelines, AWS SageMaker, SageMaker Studio).
• Expertise in deploying and maintaining machine learning models in production.
• Deep understanding of the machine learning lifecycle, including model versioning, monitoring, retraining, and CI/CD.
• Familiarity with data engineering concepts (ETL pipelines, data warehousing).
• Strong analytical and problem-solving skills.
• Excellent communication and presentation skills.
• Proven experience leading data science teams and projects.

Qualifications:

• Minimum 5 years of hands-on data science experience with focus on machine learning, generative AI, and MLOps.
• Master's or Ph.D. in a relevant field.

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