• Verifying, investigating and remediation of customer records in accordance with client guidelines• Identifying discrepancies between documents and client electronic records, ensuring accuratedata input and maintenance of record integrity into relevant databases• Ensuring high level of compliance to quality, system integrity and service delivery standards• Working with all stakeholders to ensure continuous improvement and process efficiencies• Maintaining sound knowledge of key processes, procedures and updated workflows

The graduate program at Monash, has assisted in not only developing but also applying data science and analytical techniques to enhance businesses by adopting appropriated decisions. The course includes Explanatory data analysis, data visualisation, Big data processing, Database management, Statistical Modelling with large data sets.• Developed an application, a complete setup from streaming to storing and analysing the data from sensors to predict and stop fire from sensors being deployed in Victorian cities. using Kafka, Apache Spark Streaming and MongoDB.• Proficient knowledge in Advanced Data Analysis and machine learning, model selection, how model's complexity is related to the accuracy and performance.• An Automatic Sentiment Classification system was built that depends on machine learning techniques to learn from a large data set provided by Yelp.• Big data processing and management techniques were developed and applied onto various large data sets along with achieving parallel databases.• Analysed Crime data of South Australia from 2010-2019 through Apache Spark andMongoDB. Distributed processing was achieved for 700k structured rows.• Presented a data visualisation project on `How Populous is India? Factors? Preventive measures?` using HTML and D3.• Worked on MongoDB to covert structured TB data from WHO for all the countries into unstructured data. R programming was used for visualisation.

• Weekly compliance data in ASAP Dataforce, exporting complied data using Excel to a suitable template, in accordance to Victorian Energy Upgrade’s requirement. • Developing dashboards and visualizations such as Heat Point maps, conducting EDA using Tableau and R (ggmap, ggplot2) for yielding valuable insights to business.• Performing predictive analysis for potential sites and customers by applying data modelling methodologies on historic data using Python (Scikit-learn)• Conducting ad-hoc responsibilities and generating reports that can effectively convey trends, patterns and predictions.• Active engagement with the stakeholders regarding any bottlenecks in the business and providing any analytical solutions to it.

Supported home loans and car loans team to enhance their business by implementing data-driven insights.• Improved loan customer retention by 15 % through Logistic Regression and Price Optimization.• Reduce loan application rejection by 10% by providing simple business rules to the loan team using Decision Tree.