5-8 years relevant work experience Understands complex deep learning architectures and must have implemented deep learning solutions hands-on Should have good understanding of Gen AI principles and basic prompt engineering In-depth knowledge of classical machine learning is necessary as well across variety of algorithms, like regression, tree based methods etc. Experience across different analytical methods like hypothesis testing, segmentation, time series forecasting, test vs. control comparison etc. Experience with unstructured data analysis, e.g. call transcripts, using Natural language Processing (NLP)/ Text Mining Experience in financial services Exposure to Gen AI designs like RAG etc. Understanding of Agentic workflows is a plus Proficient in data science and machine learning concepts with the mathematics behind them Must have experience in implementing the Data Science knowledge in actual industry projects Proficient in formulating analytical methodology, identifying trends and patterns with data Has the ability to work hands-on to retrieve and manipulate data from big data environments Proficient in Python/R, SQL, Pyspark Proficient in TensorFlow, Keras, Pytorch and more advanced DL frameworks Proficient in MS Excel, PowerPoint Experience with LLMs like Gemini/GPT/Llama etc. Experience with Tableau Strong analytical and problem-solving skills Excellent communication and interpersonal skills Be organized, detail oriented, and adaptive to matrix work environment ------------------------------------------------------ For complementary skills, please see above and/or contact the recruiter. ------------------------------------------------------