Principal/Lead Data Scientist

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Qualifications

• Bachelor's or Master's degree in Data Science, Computer Science or a related field.
• Minimum 11-15 years of experience in AI and Machine Learning
• Strong proficiency in Python, PySpark, cloud platforms such as AWS, Azure and GCP
• Strong proficiency in machine learning, deep learning, supervised/unsupervised learning algorithms and their execution
• Good to have experience and understanding of Generative AI concepts
• Previous experience in leading data science projects is must
• Previous experience in new/ renewal business development is must
• Previous experience in client and internal team management is must
• Hands-on experience with model training, hyperparameter tuning, and deployment.
• Excellent problem-solving skills and attention to detail.
• Strong communication and teamwork skills
• If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!
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Responsibilities

• Leading AI solution end – to – end in given client projects, including AI solution design, execution and client and team management
• Leading project teams through the solution development, validation and, deployment, monitoring ensuring deliverable quality and timeliness
• Solving internal and client deadlocks ensuring alignments on key technical aspects of the AI solution
• Partnering with Sales teams during new business and renewal business development conversations to ensure new and incremental business
• Manage reporting team of data scientists and Sr. Data scientists providing career guidance for growth, resolving issues and ensuring high utilization in client projects
• Providing regular updates to executive team on client projects being handled, calling out project status, risks, issues, resolutions from a technical pov
• Collaborate with other functional teams such as Engineering, MLOps, DevOps, etc. as required in the client projects ensuring clear and effective communications enabling integration of AI solutions into client production systems.
• Collaborate with internal and client stakeholders to understand business requirements and translate them into AI solutions.
• Ensure optimizations in code and model using best-in-class techniques in ML and Deep learning
• Lead process of extensively clean, preprocess and transform to raw datasets to ensure its quality and suitability for model training.
• Implement best practices throughout the design and execution of AI solution