What you will be doing: As a part of the Global Credit Risk and Data Analytics team, this person will be responsible for carrying out analytical initiatives which will be as follows: - Dive into the data and identify patterns Development of end-to-end Credit models and credit policy for our existing credit products Leverage alternate data to develop best-in-class underwriting models Working on Big Data to develop risk analytical solutions Development of Fraud models and fraud rule engine Collaborate with various stakeholders (e.g. tech, product) to understand and design best solutions which can be implemented Working on cutting-edge techniques e.g. machine learning and deep learning models Example of projects done in past: Lazypay Credit Risk model using CatBoost modelling technique ; end-to-end pipeline for feature engineering and model deployment in production using Python Fraud model development, deployment and rules for EMEA region Basic Requirements: 1-3 years of work experience as a Data scientist (in Credit domain) 2016 or 2017 batch from a premium college (e.g B.Tech. from IITs, NITs, Economics from DSE/ISI etc) Strong problem solving and understand and execute complex analysis Experience in at least one of the languages - R/Python/SAS and SQL Experience in in Credit industry (Fintech/bank) Familiarity with the best practices of Data Science Add-on Skills : Experience in working with big data Solid coding practices Passion for building new tools/algorithms Experience in developing Machine Learning models
What you will do:As a Data Science Lead, you will be working on creating industry first analytical and propensity models tohelp discover the information hidden in vast amounts of data, and make smarter decisions to delivereven better customer experience. Your primary focus will be in applying data mining techniques, doingstatistical analysis, and building high quality prediction systems integrated with our products.➢ Working with business and leadership teams to gathering and analyse structured and unstructured data➢ Data mining using state-of-the-art methods➢ Enhancing data collection procedures to include information that is relevant for building analyticsystems➢ Processing, cleansing, and verifying the integrity of data used for analysis➢ Doing ad-hoc analysis and presenting results in a clear manner➢ Creating automated anomaly detection systems and constant tracking of its performance➢ Creation and evolution of an efficient BI pipeline into a multi-faceted pipeline to support variousmodelling needs.What we are looking for:➢ 5-8 years of relevant experience, preferably in financial services industry.➢ A bachelors / master’s degree in the field of Statistics, Mathematics, Computer Science orManagement from Tier 1 Institutes.➢ Data warehousing experience will be a plus.➢ Good conceptual understanding of statistics and probability.➢ Experience in developing dashboards and reports using BI tools.
• Act as a lead analyst on various data analytics projects aiding strategic decision making for Fortune 500 / FTSE 100 companies, Blue Chip Consulting Firms and Global Financial Services companies • Understand the client objectives, and work with the PL to design the analytical solution/framework. Be able to translate the client objectives / analytical plan into clear deliverables with associated priorities and constraints • Collect/Organize/Prepare/Manage data for the analysis and conduct quality checks • Use and implement basic and advanced statistical techniques like frequencies, cross-tabs, correlation, Regression, Decision Trees, Cluster Analysis, etc. to identify key actionable insights from the data • Develop complete sections of final client report in Power Point. Identify trends and evaluate insights in terms of logic and reasoning, and be able to succinctly present them in terms of an executive summary/taglines • Conduct sanity checks of the analysis output based on reasoning and common sense, and be able to do a rigorous self QC, as well as of the work assigned to analysts to ensure an error free output • Aid in decision making related to client management, and also be able to take client calls relatively independently • Support the project leads in managing small teams of 2-3 analysts, independently set targets and communicate to team members • Discuss queries/certain sections of deliverable report over client calls or video conferences Technical Skills: • Hands on experience of one or more statistical tools such as SAS, R and Python • Working knowledge or experience in using SQL Server (or other RDBMS tools) would be an advantage Work Experience: • 2-4 years of relevant experience in Marketing Analytics / MR. • Experience in managing, cleaning and analysis of large datasets using statistical packages like SAS, R, Python, etc. • Experience in data management using SQL queries on tools like Access/ SQL Server
• Using statistical and machine learning techniques to analyse large-scale user data, including text data and chat logs; • Applying machine learning techniques for text mining and information extraction based on structured, semi-structured and unstructured data; • Contributing to services like chatbots, voice portals and dialogue systems • Input your own ideas to improve existing processes on services and products