Venkata Sri Harsha Email & Phone Number

Plano, Texas, United States

Responsible for analyzing large sets of data to draw conclusions and make recommendations to the business using statistical models. Involved in discussions with business teams to understand the business process mapping and came up with business use cases to improve sales, predictive product market penetration using ML models. Worked closely with project managers to develop and expand business use cases ideas for implementations. Used XGBoost model to identify the… Show more Responsible for analyzing large sets of data to draw conclusions and make recommendations to the business using statistical models. Involved in discussions with business teams to understand the business process mapping and came up with business use cases to improve sales, predictive product market penetration using ML models. Worked closely with project managers to develop and expand business use cases ideas for implementations. Used XGBoost model to identify the features that predict the sales metrics and KNN algorithm to generate a comparable set of accounts that behave similarly. Used AWS S3 bucket to load the data from SQL database. Worked in development of product penetration model enhancements that is deployable and schedulable in AWS sage maker and Amazon Code Pipeline. Created End to End ML models based on State rules to handle unique rules around account purchase patterns and regulations. Worked in generalizing model to streamline penetration evaluation for a user driven product. (Brands, Sku groups, Product types etc.) Lead the evaluation and inclusion of appropriate affinity metrics in penetration based on region and account demographics. Deployed 10+ models of product penetration models in AWS cloud platform by implementing diverse Amazon pipelines catering to multiple regions. Leveraged ChatGPT API to process audio, video, text files and generated themes, summary, sentiment score and weekly customer sentiment reports for customer service center directors. Involved in fast paced & complex demand sensing program to acquire data from 20+ external sources and 25+ internal sources and then cleansed data, scaled features, reduced dimensions then ingesting data sets in into data bricks environment. Crafted models to accurately predict (less 7% variance) the demand for upcoming 12 months including safety stock and dead stocks. Derived specific features based on feature importance which contributes to dead stocks and eventually reduction in it. Show less

Tulsa, Oklahoma, United States

• Responsible for performing Machine-learning techniques regression/classification to predictthe outcomes.• Used Python to get the data in right format, which used by other internal applications to calculate the thresholds.• Utilized machine-learning algorithms such aslogistic regression, multivariate regression, Kmeans, & Recommendation algorithms for data modelling.• Involved in team meetings and discussions with business teams to understand the business use… Show more • Responsible for performing Machine-learning techniques regression/classification to predictthe outcomes.• Used Python to get the data in right format, which used by other internal applications to calculate the thresholds.• Utilized machine-learning algorithms such aslogistic regression, multivariate regression, Kmeans, & Recommendation algorithms for data modelling.• Involved in team meetings and discussions with business teams to understand the business use cases.• Worked with Data Engineers and Data Analysts to understand and gather specificrequirements and extract relevant business stories.• Used Python, SQL to create Statistical algorithms involving Multivariate Regression, Linear Regression, Logistic Regression, PCA, Random Forest models, Decision trees, Support Vector Machine for estimating the risks of welfare dependency.• Used Azure HD Insight for Data analysis to meet the requirements. Used neural networks to build deep learning CNN models.• Collaborated with database engineers to implement ETL process, wrote and optimized SQLqueriesto perform data extraction and merging from SQL server database.• Worked in creating different visualizations in Tableau using Bar charts, Line charts, Pie charts,Maps, Scatter Plot charts, and Table reports.• Developed NLP with Deep Learning algorithms for analyzing text improving over their existingdictionary-based approaches • Creating browser-based visualization tools and dashboards using Tableau• Using Gitlab repository to clone the code and commit the changes and push it to the developbranch from feature branch. Employed statistical tests such as hypothesis testing, t-test, confidence intervals, for error measurements.• Built RDBMS tables in cloud SQL for large datasets pulled from various sources using API's todevelop NLP machine learning models. • Data cleaning, Exploratory data analysis, Data Wrangling and preprocessing data using PandasNumPy and data visualization Show less

Hyderabad, Telangana, India

• Performed Exploratory Data Analysis (EDA) to maximize insight into the dataset, detect the outliers and extract important variables numerically and graphically.• Applied concepts of probability, distribution, and statistical inference on the given dataset to unearth interesting findings using comparison, T-test, F-test, R-squared, P-value etc.• Analyzed data to identify glitches and cleaning it to reduce the distortions.• Performed various data manipulation techniques in… Show more • Performed Exploratory Data Analysis (EDA) to maximize insight into the dataset, detect the outliers and extract important variables numerically and graphically.• Applied concepts of probability, distribution, and statistical inference on the given dataset to unearth interesting findings using comparison, T-test, F-test, R-squared, P-value etc.• Analyzed data to identify glitches and cleaning it to reduce the distortions.• Performed various data manipulation techniques in statistical analysis like missing data imputation, indexing, merging, and sampling.• Performed Training, Test and Evaluated the model on a cloud Platform Azure ML after building the predictive model. Normalized the data and transformed all the values to a common scale.• Visualize, interpret, report findings & develop strategic uses of data Using Python, Tableau.• Built advanced Machine Learning classification models like KNN, SVM and clustering algorithms Hierarchical Clustering.• Performed univariate and multivariate analysis on the data to identify any underlying pattern in the data and associations between the variables.• Performed data cleaning and worked with developers to ensure the integrity of the data pipeline.• Worked with key stakeholders to ensure all telemetry and appropriate KPIs are tracked and analyzed.• Using NLP techniques identified possible matching words that can provide a base to categorize the protocol of required words • Analyzing of positive, Negative and Neutral sentiments of the consumers to provide a base to the predictive model.• Responsible for Data Cleaning, features scaling, features engineering by using NumPy and Pandas in Python.• Collaborated with database engineers to implement ETL process, wrote and optimized SQL queries to perform data extraction and merging from SQL server database. Show less

Hyderabad, Telangana, India

• Compiled data from various sources public and private databases to perform complex analysis and data manipulation for actionable results.• Worked closely with the Data Governance Office team in assessing the source systems for projectdeliverables. • Used SQL queries to pull the data from disparate systems and Data warehouse in different environments.• Worked on data pre-processing and cleaning the data to perform feature engineering and performed data imputation… Show more • Compiled data from various sources public and private databases to perform complex analysis and data manipulation for actionable results.• Worked closely with the Data Governance Office team in assessing the source systems for projectdeliverables. • Used SQL queries to pull the data from disparate systems and Data warehouse in different environments.• Worked on data pre-processing and cleaning the data to perform feature engineering and performed data imputation techniques for the missing values in the dataset.• Creating aggregates, filters, quick filters, calculated measures.• Designed and deployed reports with drill up and drill down menu options and linked reports using Tableau.• Performed financial product cost/benefit analysis to support Credit Union senior management in financial product development and management.• Presented DQ analysis reports and score cards on all the validated data elements andpresented- to the business teams and stakeholders.• Involved in defining the Source to Target data mappings, business rules, data definitions. Successfully interpreted data to draw conclusions for managerial action and strategy.• Used statistical techniques for hypothesis testing to validate data and interpretations.• Collaborated with various business stakeholders to create Business Requirement Document(BRD), translated gathered high-level requirements into a Functional Requirement Document (FRD) to assist implementation side SMEs and developers, along with data flow diagrams, user stories and use cases Part of a Scrum Agile team.• Applied concepts of probability, distribution, and statistical inference on the given dataset to unearth interesting findings using comparison, T-test, F-test, R-squared, P-value etc.• Used Excel and Tableau to perform different analysis like descriptive, exploratory, and predictive to get the insights of data more accurately. Show less