About the Role The Consumer Model Development Centre, within CDAI organization, is looking for Quantitative analytics specialist to join our team and help us solve challenging and interesting business problems through data exploration, advanced analytics and visualization. In this highly valued role, you will be working on ML/AI models within the Center of Excellence (COEs) with varied competencies, including Developing Models, Monitoring, Deployment, and Analytic Quality Review. This role is highly hands on position in the area of ML/AI and Data science across. Responsibilities Required to work individually or as part of a team on data science projects and work closely with business partners across the organization. Perform various complex activities related to statistical/machine learning. Provide analytical support for developing, evaluating, implementing, monitoring and executing models across business verticals using emerging technologies including but not limited to Python, Spark, and H2O etc. Ability to work with large datasets using SQL and present conclusions to key stakeholders. Establish a consistent and collaborative framework with the business and act as a primary point of contact in delivering the solutions. Build quick prototypes to check feasibility and value to business. Develop and maintain modular code-base for reusability Review and validate models and help improve the performance of the model under the preview of the banking regulations. Work closely with technology teams to deploy the models to production. Prepare detailed documentations for projects for both internal and external that complies regulatory and internal audit requirements Required skills: 2+ years of Quantitative Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education Master's degree or higher in statistics, mathematics, physics, engineering, computer science, economics, or quantitative discipline Desired Skills Bachelors or Master's degree in Engineering field like computer science, Information technology, Electrical Engineering etc. M.Sc./M.Phil. in statistics/economics/mathematics/ operations research engineering physics 3-5 years of relevant hands on experience in data science and advanced analytics. Must have hands on exposure in Python and SQL. Working knowledge of libraries like, sckit-learn, pandas, numpy, mllib, matplotlib, keras Proficiency in data mining and statistical analysis. Experience in developing, implementing models. Statistical models linear regression, logistic regression, time series analysis, multivariate statistical analysis Machine learning models Random forest, XGBoost, GBM, SVM Exposure to deep learning framework - ANN,RNN, CNN, LSTM Excellent understanding of model metrics including AUC, ROC, F-statistics etc. with clear understanding of how model performance is tuned Strong programing skills. Exposure in one or more of Big Data skills SQL, Aster, Teradata, Hadoop, SPARK, H20, BigQuery. Exposure to Google Cloud Platform Critical thinking and strong problem solving skills Ability to learn the business aspects quickly Knowledge of banking industry and products in at least one of the LOB such as credit cards, mortgage, deposits, loans or wealth management etc.is desirable Knowledge of functional area such as risk, marketing, operations or supply chain in banking industry is desirable Ability to multi-task and prioritize between projects Ability to work independently and as part of a team Working expertise in Tensorflow, Keras or Pytorch would be added advantage
