Senior Data Scientist

• A strong level of proficiency in python programming
• Practical knowledge and working experience on Statistics and Operation Research methods
• Practical knowledge and working experience in tools and frameworks like Flask, PySpark, Pytorch, TensorFlow, keras, Databricks, OpenCV, Pillow/PIL, streamlit, d3js, dashplotly, neo4j
• Hands on experience in Analytics/AI-ML AWS services like SageMaker, Canvas, Bedrock
• Good understanding of how to apply predictive and machine learning techniques like regression models, XGBoost, random forest, GBM, Neural Nets, SVM etc
• Proficient with NLP techniques like RNN, LSTM and Attention based models and effectively handle readily available stanford, IBM, Azure, Open AI NLP models
• Good understanding of SQL from a perspective of how to write efficient queries for pulling the data from database
• Hands on experience on any version control tool (github, bitbucket)
• Experience of deploying ML models into production environment experience (MLOps) in any one of the cloud platforms like Azure and AWS
• Understanding business needs / mapping it to the business processes
• Hands on experience in agile project delivery
• Good in conceptualizing and visualizing end to end business needs both at high level as well as detailed
• Good in articulating the business needs
• Good analytical and problem-solving skills
• Good communication, listening and probing skills
• Strong inter-personnel skills
• Should collaborate with other team members and work as team

Job Description:

• Comprehend business issues and propose valuable business solutions
• Design Factual or AI/profound learning models to address business issues
• Design Statistical Models/ML/DL models and deploy them for production
• Formulate what information is accessible from where and how to augment it
• Develop innovative graphs for data comprehension using d3js, dashplotly and neo4j
• Preferred Certification: (Good to have)AWS Specialty Certification in Data Analytics, Machine Learning