Business Analytics Manager

• Nov 2021 - Present

Senior Consultant - Analytics

• Feb 2019 - Oct 2021

•Provide analytical and thought leadership to other BI/Data Science Analysts/Data Engineers to explore new areas for fresh business insights. •Hands-on experience in Linear regression, Logistic regression, Decision tree, Predictive Modelling, Clustering, Hypothesis testing, Scoring, Ranking, Anova, Neural Networks & Adobe Analytics. •Data analysis and periodic reporting on various E-commerce metrics such as profitability, GMV, Margin and Orders. •Analyze and extract relevant information from large amounts of data from various sources using SAS/R/Python. •Very good understanding of incremental models, Uplift models, HVG, SOW models in campaign and marketing. •Working with an advanced analytics team in building two-stage models, ZIP and scoring models on various projects. •Exposure in defining business problems, work with and manipulate data, develop Data Science and analytical algorithms & solutions, and develop analytical models into production environments. •Gained a conceptual exposure on the application of the relevant industry Data Science methods driving data-driven business decisions across the organization and building a data-driven culture & policies •Keen analyst with efficiency in gathering and understanding requirements of clients & other multiple stakeholders (at strategic and tactical levels), followed by a translation into functional specifications as well as provisioning of suitable business-driven data solutions •Establish scalable, efficient, automated processes for large scale data analyses, develop models to find patterns, validate and prototype the model. •Ability to develop experimental and analytic plans for data modeling processes, use of strong baselines, ability to accurately determine cause and effect relations. •Large scale data mining to find trends and problems, then communicate and drive corrective action. •Performing Error handling by investigating the root cause of the errors and proposing solutions for the errors. Show less

Assistant Manager - Analytics

• Aug 2017 - Feb 2019

• Working in campaign analytics team for leading US hotel chain.• Analyze and extract relevant information from large amounts data from various sources.• Hands-on experience in predictive modelling and analysis.• Provide analytical and thought leadership to other BI/Data Science Analysts/Data Engineers to explore new areas for fresh business insights.• Establish scalable, efficient, automated processes for large scale data analyses, develop models to find patterns, validate and prototype the model.• Ability to develop experimental and analytic plans for data modeling processes, use of strong baselines, ability to accurately determine cause and effect relations.• Large scale data mining to find trends and problems, then communicate and drive corrective action.• Develop queries for ad-hoc requests and projects, as well as ongoing reporting.• Working on market content targeting (MCT) strategy. Collecting data, analyze, build dashboards and report to provide insights and recommend changes and improvements in communication strategy. Show less

Senior Analyst

• Aug 2016 - Jul 2017

ISM

• Jan 2014 - Jun 2016

• Experience in SAS/Base, SAS/Macro, SAS/Sql, Sorting, printing and summarizing data in SAS, extracting data from the database using SAS procedures creating SAS data sets. • Creation of Queries for ad-hoc requests of senior management. • Working on numerous analytical problems in marketing, communication. From procuring data, cleaning data, developing models, drawing insights which help to formulate new marketing and communication strategies. • Working on reports, exploratory data analysis and providing data to various teams to develop models. • Site wide investigation of Fraud, Risk and Abuse cases. • Hands-On knowledge on SAS, R, MS SQL Server, Excel, VBA automation. Show less

Business Analyst

• Jun 2012 - Dec 2013

• Excellent analytical and problem-solving skills, including the ability to dis-aggregate issues, identify root causes and recommend solutions by application of statistical methods and ML techniques • Ability to mine massive data volumes - data manipulation, data cleansing, pattern matching etc • Track and make suggestions for ways to improve upon KPIs (Key Performance Indicators) • Analysis around identifying at-risk or lapse customers, potential prospect customers, existing customers to up-sell/cross- sell Omega products and using propensity models to identify customers most likely to get re-activated. Show less