About

Anil Panda is a highly skilled Senior Data Scientist at ING Bank, with over 11 years of experience in the field of data science and machine learning. He is responsible for creating, productionizing, and maintaining machine learning models and frameworks that focus on financial and non-financial risk and pricing. Anil has expertise in ML interpretability, fairness, and validation techniques, which he applies to his work at ING Bank. Anil's previous experience includes working as a Data Scientist & Machine Learning Engineer at both ING Bank and TCS. At TCS, he created and productionized a classification model in Hive, Pyspark, Python & Unix, which reduced the false alerts generated by the existing anti-money laundering system by 35%. He also streamlined & deployed an ML model for the Retail Risk department, reducing feature creation and training time from 8 hrs to 2 hrs. Additionally, he designed and implemented an Advanced Analytics Framework (AAF) using Pyspark, Python, Unix & Hbase, which reduced the time to market from 6 weeks to 2 weeks. Anil has hands-on experience in setting up various ML environments within the bank, including Hadoop clusters (Hortonworks HDP, IBM Biginsights), RStudio servers, H2o AI, and Anaconda components. He has also trained ~30 colleagues in big data ecosystem tools via classroom training. Anil holds a Bachelor of Engineering (B.E.) degree in Information Technology from Shah and Anchor Kutchhi Engineering College, Mumbai, and completed his HSC from Bhavans College, Andheri, Mumbai. He is proficient in several technologies, including Data Scientist, Research Scientist, ML, Python, AI, Spark, Big Data, Hadoop, and Apache Hive. Overall, Anil Panda is a highly skilled Senior Data Scientist with extensive experience in the field of machine learning and data science. He has a proven track record of creating and productionizing ML models and frameworks, and his expertise in ML interpretability, fairness, and validation techniques makes him a valuable asset to any organization.