Latha V Email & Phone Number

Frisco, Texas, United States

• Initiated the project of data migration from Amazon Redshift to Snowflake for data incoming from Salesforce, SharePoint and ServiceNow using Informatica Cloud.• Designed a two-way synchronized loading mechanism for Enterprise Data Warehouse to load data into/from Snowflake from SQL Server.• Prepared structured data for Tableau dashboards from the migrated data and designed new dashboards for reporting purposes.• Deployed and optimized big data streaming service (Flink and Kafka)• Assisted Business Intelligence and Data Engineering teams on data investigation, interpreting variables, deciding on proof of concepts and synthesized complex information to frame and answer important data questions• Planed team's roadmap , designed and built Streaming and Batching recommendation models across multiple teams • Used complex SQL queries, tools and techniques to explore given datasets and databases for data cleansing and preparation for further Data Analysis• Utilized my proficiency in building Machine Learning models in Python and proficiency in cloud infrastructure to perform tasks related to all aspects of model development, including ETL (Extract, Transform, Load) operations, data cleansing, predictive analysis, model build and deployment• Designed scalable, efficient, automated processes for large scale data analysis, model development, validation and implementation with end-to-end Machine Learning pipelines

Dallas, Texas, United States

Performed risk assessment by deriving insights from customer data and developing a risk scorecard for suppliers• Used Predictive Analytics and Machine Learning to forecast company sales of new products with 85% accuracy• Performed feature analysis of suppliers’ data, used unsupervised algorithms like clustering to detect anomalies/outliers and developed fraud detection algorithms for industry customers• Used Principal Component Analysis in feature engineering to analyze high dimensional data • Derived insights from datasets and developed KPI dashboards to present them to stakeholders using Tableau• Wrote complex SQL queries and procedures to extract relevant data from the system’s database• Performed Data Cleaning, features scaling, features engineering using pandas and Numpy packages in python using data blending, action filters and parameters, created interactive data visualizations and storyboards in Tableau• Mentored two new team members and taught project policies and project workflow, performed knowledge transfer role for newcomers by teaching them Python and SQL

Dallas, Texas, United States

• Work with the statistician team to conduct the hypothesis testing for the research (parametric and nonparametric test, logistic regression, permutation test)• Check the data cleaning process and validated the data accuracy (maker checker check list)• Build the automation algorithm for data merging and statistical analysis using Python (pandas, scipy, matplotlib, statistics)• Construct the interactive App using R (R shiny). Collaborated with top pharmaceutical companies using to produce informative results• Analyzed large-scale datasets and performed statistical modeling using various tools (SAS/Python/SQL/R)•Implement machine learning methodology for claim research. Manage team's workload, QC the code, and provide results for DBs. Worked with statisticians to create the hypothesis testing• Applied logistic regression to develop a decision support tool, which considered variables such as demographic data, values of genes and clinical tests

New Jersey, United States

• Created and designed reports that will use gathered metrics to infer and draw logical conclusions of past and future behavior• Performed market analysis to efficiently achieve targeted marketing objectives improving sales by 20%• Worked on a ML algorithm using Isolation Forests to detect referral coupon fraud improving accuracy by 15% from an earlier prediction model sales by 20%• Used data cleaning techniques to fine tune customer data and used Random Forest algorithm to help identify loyal customers and predict the likelihood of customers buying a recommended product• Processed industry datasets in Hadoop and further analyzed in Apache Hive to optimize model parameters • Performed data analysis to determine critical factors in MATLAB using data blending, action filters and parameters, created interactive data visualizations and storyboards in Tableau