Asset maintenance optimization for an Oil & Gas client which involves survival analysis and distribution fitting on historical equipment failure data. Survival analysis is conducted using parametric (Weibull and exponential distribution) as well as non-parametric (Kaplan-Meier) techniques. Electricity load and price forecasting for a large Utility client using time series (ARIMA, TBATS) as well as predictive modelling (ANN, regression, etc) methods. For this project data was read from Hive and output was stored in PostgreSQL.Experience in data preprocessing, data analyses, model development, validation and deployment on cloud.Worked in distributed agile setup.Liaised with key stakeholders for requirement gathering, progress communication, solution demonstration and solution handover.Managed a 4 membered team.

Created proof of concepts and dashboards to showcase analytics capabilities

Utilities Sector, Retail and CPG Sector• Responsible for preparing and delivering value-adding industry research and thoughtleadership for the partners in consultancy firm• The reports focus on key industry challenges and corresponding solutions that can be offered to clients in the areas of finance, strategy, and operational improvements• Prepared company briefs, covering industry trends, company strategies, company issues, financial analyses, competitor benchmarking and POV’sAnalytics Capabilities• Worked on a project to estimate rate of incorrect data in CRM database of a key client using a sampling technique and hypothesis testing• Currently working on campaign data of a key client with an objective to improve response rate to campaigns. We have planned to use logistic regression using R to create an effectiveness model for this study

• Built financial models from scratch , modeling the forecasts and sensitivity of assumptions• Conducted stock valuation. Undertook financial and business analysis of tracked companies• Prepared sector presentation and stock pitch for marketing to clients • Undertook in-depth secondary research to identify sector trends and compare business strategies, business performance and revenue drivers of various companies• Built a scenario analyzer in which the effect of change in revenue driver can be seen on key financial items like earnings, FCF and net debt• Worked on number of thematic reports, earning reviews and previews

• Created handbook of SEZ policies in India along with SEZs distribution pattern in India• Identified SEZs which are more beneficial to the Indian Economy• Quantified Fiscal Benefits received by an IT company in SEZ and compared its earnings with business units in STP and DTA