Data Science Consultant

As a Data Scientist at Infosys Consulting, you will be part of a specialized customer-facing AI Labs team within the Automation & Artificial Intelligence Consulting Practice. Your role will involve working closely with AI Consultants and SMEs to define and deliver best-in-class solutions. You should be entrepreneurial, possess strong design skills, be highly analytical, emotionally intelligent, a team player, and driven by making a meaningful impact through your work. This role offers exceptional opportunities for personal growth and recognition for your contributions to developing new opportunities and thought leadership in artificial intelligence and automation domains. - Establish productive long-lasting working relationships with a variety of stakeholders - Lead data pipeline design with strong analytical skills and attention to detail - Work with a variety of Data Science tools, new technologies, IT, compliance, security issues - Design and develop technology solutions across multiple client engagements - Collaborate with other teams to understand business requirements and ensure seamless transitions - Work closely with AI and Fortune 500 clients to build solutions and define AI strategy - Utilize strong logical structuring and problem-solving skills to turn data into actions - Demonstrate strong verbal, written, and presentation skills - Apply programming skills and understanding of data science and Machine Learning tools - Collaborate on high-impact initiatives with Data Scientists globally - Bachelor's or master's degree/PhD in Statistics, computer science, information technology, or related field - Solid understanding of Statistics, hypothesis formulation, testing, descriptive analysis, data exploration - Expertise in Python or R - Strong experience in machine learning algorithms such as Linear/Logistic regression, Random Forest, SVM, Neural Networks, Deep Learning (CNN, RNN, LSTM) - Exposure to NLP and Computer vision use cases - In-depth knowledge of neural networks and architectures - Familiarity with the latest DL architectures and toolkits/frameworks/libraries like Pytorch, TF/Keras, Scikit-Learn, BERT - Experience in Machine Learning Lifecycle - Data Processing, Algorithm Benchmarking, Validation - Exposure to building AI models from scratch - Exposure to Graph-based databases is a plus - Experience with relational databases,