Senior Data Scientist

Key Skills

AI technology, Analytical and Problem solving, Keras software library, Large Language Models - LLMs, Machine learning techniques, MLOps tools, NumPy, Pandas, Python Programming, Scikit-learn, TensorFlow

Job Description

We are looking for a highly capable Senior Data Scientist to build AI based solutions, systems and use cases for Comviva.

As a senior Data Scientist, he/she will be working closely with different product units to understand the business use cases and challenges faced. Define production grade solutions, measurable AI solution metrics and tools stack. Assist in defining customer facing solutions.

Senior Data Scientist should be fundamentally strong in statistics and mathematics for data science. Candidate should have exposure of end-to-end data science project life cycle. Candidate should be able to research new technology areas, propose applicability to Comviva products & solutions, and ways to adopt the new technology. Candidate must have a proven ability to drive business results with data-based insights.

Prior experience in building production grade ML models and MLOps best practices is important.

Responsibilities

• Understand AI/ML use cases generic as well as product specific.
• Developing new Machine Learning models for the use cases
• Work with ML Engineers to define MLOps best practices and tool stack
• Deploy the analytics and predictive models in production environment
• Monitor deployed models and define model evaluation and performance metrics to maintain models.
• Mentor team members and build next level
• Write technical documentation

Must Have:

• Proven experience in end-to-end data science project life cycle
• Excellent problem solving and analytical skills
• Fundamentally strong in statistics and mathematics for data science
• Excellent understanding of machine learning techniques and algorithms for text analysis, multimodal AI, supervised as well unsupervised techniques
• Experience with Python and common data science toolkits like Jupyter, Pandas, Numpy, Scikit-learn, TensorFlow, Keras etc.
• Knowledge on ensemble techniques like bagging, boosting

Nice to have

• Prior experience in working on LLMs, GAN, cloud based AI
• Experience in deep learning, neural networks
• Experience in data science project for time series data or AIOPS space
• Experience working with data fabric, feature stores, data versioning