Santosh R Email and Phone Number

• Built the Decision System by creating the algorithm based on business data.• Performed data ETL by collecting, exporting, merging and massaging data from multiple sources• Used Optimization Technique Simulated Annealing and Decision Tree ML concepts. Statistical concepts were widely used including Central Limit Theorem, Probability Concept, Probability Distribution (Binomial, and Poisson Distribution)• Built Decision Trees in Python to represent segmentation of data and identify key variables to be used in predictive modeling• Evaluated models using Cross Validation and Confusion Matrix.• Addressed overfitting by implementing cross validation methods like K-Fold.• Assisted the business with claims analysis by building Instant Decision Rules with the help of A/B Testing in the Claims Adjudication System• Managed project planning and deliverables for several projects focused on Advanced Analytics, Big Data and Digital Analytics streams• Managed offshore and onshore team workloads for project deliverables• Provided ad hoc support to senior management on project and technical issues• Provided support in solution development for data science, advanced analytics and digital analytics projects • Guided team of data scientists to develop statistical models and algorithms to address complex business problems• Implemented machine learning techniques and interpreted statistical results which are ready- consumption for senior management and clients • Provided pre-sales support to team for RFP’s, RFI’s and client presentations• Played a vital role in claims analysis, assisting the business in decision making for Claims Processing • Generated reports in case of Decline Claims using Tableau

• Developing analytical databases from different sources and create a master data set.• Responsible for data identification, collection, exploration, cleaning for modeling.• Performed Time Series Analysis on data in order to extract meaningful statistics and other characteristics of the data to predict future values based on previously observed values. • Determined customer satisfaction and helped enhance customer experience using NLP.• Manage large data sets from a wide variety of sources and apply analytics and statistical analyses to support health projects and products. • Implementing analytics algorithms in Python.• Performed training Natural Language models and reinforcement learning engines to optimize intelligent agents that automate task execution. • Performed k-Means clustering in order to understand customer itemized bought products and segment the customers based on the customer products for animal medicine and vaccines behavior information for customized product offering, customized and priority service, to improve existing profitable relationships and to avoid customer churn, etc using Python. • Performed Text analytics on unstructured email data using Natural language processing tool kit (NLTK). • Worked with text to vector representation methods including Counter Vectorizer, Tf-idf for topic modelling.• Applying Clustering algorithms to group the data on their similar behavior patterns. • Work with data analytics team to develop time series and optimization.• Experienced in data scraping.• Used PySpark Machine learning library to build and evaluate different models.• Created various Proof of Concepts (PoC) and gap analysis and gathered necessary data for analysis from different sources, prepared data for data exploration using data munging.• Used Tableau to generate reports with internal records, secondary sources of data, JSON, CSV and more. Which helped the support team for better marketing.

• Understanding business context and strategic plans and develop a data-driven business plan to support the attainment of business goals.• Created a dataset using SQL Teradata complex queries along with identification to factors to customers calling to customer care from customer care text repository.• Data manipulation/treatment based on nature of data (for example missing value imputation, Information Value (IV), Weight of Evidence (WOE), Data profiling, correlation matrix, relative importance between predictors, variable clustering, univariate and bivariate plots, etc.)• Building predictive models from start-to-finish following CRISP-DM life cycle (i.e. extract data, manipulate data, Data Profiling, build and validate model) and then deployed model using flask.• Preparation of final project presentation documents for overall significance of the project in a well- defined manner• Identify the most significant behavioral patterns that lead to customer churn and build an attrition model using Random Forest, SVM with Precision-Recall curve as evaluation metric for the model.• Build a model to check the factors affecting the termination of employees and their reasons for termination using various dimension reduction techniques.• Predict the employees who are high risk to maintain the talent pool and to effectively retain talent at every level (High Potential and High performer)• Responsible for working with stakeholders to troubleshoot issues, communicate to team members, leadership and stakeholders on findings to ensure models are well understood and optimized.• Data exploration to make the data useable for building data insights and initial hypothesis.• Used the analysis of behavior and characteristics of terminated employees to drew the important factor for attrition.

• Responsible for reporting of findings that will use gathered metrics to infer and draw logical conclusions from past and future behavior.• Implemented and managed several ETL projects using Informatica PowerCenter by loading data from a variety of Data sources like flat files, JSON, XML files to Oracle for reporting. Source and target data were synced using Informatica and finally transformed data was stored in staging tables.• Performed Multinomial Logistic Regression, Random Forest, Decision Tree, SVM to classify package is going to deliver on time for the new route.• Created reporting tables for comparing source and target data and report data discrepancies (mismatch, missing scenarios) found in the data.• Performed validations not received in the requirement document from the customer end and learnt the SQL queries which helped to attend defect triage calls.• Results obtained from report mappings were displayed using MicroStrategy which is a better User Interface tool.• Implemented rule-based expertise system from the results of exploratory analysis and information gathered from the people from different departments.• Created test plans for conducting unit testing of developed code.• Created deployment groups in QA environment and deployed workflows from DEV to QA environment.• Performed debugging of the code as per inputs given by IST (Integrated System Testing) team and deployed code into PROD environment after receiving approval from IST team.• Created and maintained complete documentation of project from beginning till end.• Performed internal enhancements of the jobs running in PROD environment.• Successfully maintained and managed all the jobs running in production environment by offering production support.• Extensive hands on experience of HP Quality Center tool used for performing production support activities