Srujana M

• Around *+ years of IT experience as a Data Scientist/Data Analyst, including profound expertise and experience in statistical data analysis such as transforming business requirements into analytical models, designing algorithms and strategic solutions that scale across massive volumes of data.

• Experienced in requirement analysis, application development, application migration and maintenance using Software Development Life Cycle (SDLC). Adequate knowledge and working experience in Agile & Waterfall methodologies.

• Involved in data science project life cycle, including Data acquisition, Data Cleaning, Data Wrangling, Data Warehousing, Data Mining, Applying Machine learning algorithms, Data Validation and Data Visualization.

• Hands on experience of statistical modeling techniques such as: Linear Regression, Lasso Regression, Logistic Regression, Time Series Analysis, Elastic Net, Factor Analysis, Clustering Analysis and Bayesian Inference.

• Professional working experience in Machine Learning algorithms such as LDA, Linear Regression, Logistic Regression, K-NN, GLM, SVM, Naive Bayes, Random Forests, Decision Trees, Neural Networks and Clustering.

• Working knowledge on Outlier detection and Treatment, Recommender Systems Dimensionality Reduction techniques and Clustering methods.

• Worked on Feature Scaling, Feature Engineering, Modeling and Evaluation.

• Employed model evaluation metrics like R-square, Confusion matrix, ROC curve, Precision, Recall, A/B testing and K- fold cross validation to validate the model’s performance.

• In - depth knowledge in programming languages Python and SQL.

• Experience in creating Dashboards and visualization charts using Tableau, Power BI and Python

(Matplotlib, Seaborn, Bokeh and Dash).

• Extensively used Python libraries Pandas for Data Munging, NumPy and SciPy for numerical and scientific computations.

• Experienced in writing complex SQL Queries like Stored Procedures, triggers, joins and Sub Queries.

• Experience in working with various Relational Databases like MySQL, MS SQL and NoSQL databases like MongoDB.

• Experienced in Data Integration Validation and Data Quality controls for ETL process and Data Warehousing using MS Visual Studio, SSIS, SSAS and SSRS.

• Automated recurring reports using SQL and Python and visualized them on BI platform like Tableau.

• Excellent communication skills, successfully working in fast-paced multitasking environment both independently and in a collaborative team and a self-motivated enthusiastic learner. PROFILE

Skills

Python, R Studio, I python notebook, R, Spyder, Databricks, AWS, Spark SQL, T- SQL, MS SQL, MySQL, MongoDB, SQL Server 2019/17/15/12, SSMS 2014, Tableau, Machine Learning Algorithms (Linear Regression, Logistic Regrsion, Random Forest, Decision Trees, Naïve Bayes, K- nearest neighbor, Hierarchial Clustering), Power BI, Qlikview, SSIS, SSAS, SSRS, Windows, Linux, M AC, Agile, Scrum, Waterfal l,M S Visio, Visual Studio, MS Access, MS Excel, MS Power P oint, MS Word, JavaScript, PL/SQL, HTML, XML, vlookup, Power Pivot, Mi crosoft Off ice, Excel Power Pivot, Excel Data Explorer, JIRA

( 319 ) 343 - 6525 add0he@r.postjobfree.com m https://www.linkedin.com/in/srujanam2020/ https://github.com/manigondasrujana Education Master’s in Business and Information Systems, New Jersey Institute of Technology Newark Dec 2018 Bachelor’s in Information Technology, Adam’s Engineering College Palvancha, India May 2010 Professional Experience

Key Accomplishments:

• Developed VBA tool (front end- MS Access and Back end- SQL Server) used by engineers for claim coding.

• Retrieve and provide warranty claims along with other critical relevant data from SQL server in a format that enables engineers to identify the failure mode and relevant CAR for each claim with at least an 80% reduction in time that would have otherwise taken.

• Developed dashboards on Tableau with data from Databricks/ SQL Server/ HANA that identifies critical path issues and lists with due dates and deliverables.

• Developed new database from scratch in SQL server for departmental use.

• Create and schedule Jobs in Databricks to update data in Tableau reports in Tableau server.

• Developed queries and automate the tasks in VBA to update and extract the data from one server to another server.

• Developed solutions for identifying patterns or trends in data to troubleshoot Aftertreatment related problems, using Telematics data and Warranty data.

• Help Engineers with SharePoint site and creating new workflows as per need.

• Developed R code to embed data in tools (Access – VBA) used by engineers.

• Used Python for Data cleaning and Predictive modeling.

• Utilize statistical and analytical methods to collect, organize, interpret and summarize data into usable information for Aftertreatment Projects, and present statistical data using charts, graphs, dashboards in meetings.

• Pull the data needed with standard query syntax; periodically identify more advanced methods of query optimization. Convert data to make it analysis ready.

• Provided performance management input for core team members. Ensure suppliers understand and can deliver to Deere’s expectations.

• Worked collaboratively and fosters effective working relationships with Internal and External stakeholders to ensure program(s) are completed according to schedule. Data Scientist

As a Data Scientist my responsibilities include predicting the failure mode of a claim by making use of history of vehicle data and data collected during lifetime of engine. This data extracted from SQL Server, Databricks, HANA and Business Objects. I am responsible to prioritize work and drive effective problem resolution. I provide tools to engineers which help them to claim code efficiently and visualize claims data and failure modes. I am also responsible for managing databases, data analysis and visualization, Data cleaning, creating dashboards, predictive modeling and building machine learning models. To achieve desired analytical output, I use Tableau – Visual analytics, R, Python – Data cleaning, machine learning algorithms(predictions), MySQL, Spark SQL, T-SQL – Querying, Data pulling. John Deere, Iowa

Sept 2019 – Current

Data Scientist

The project is to build predictive models to identify risk classification and eligibility of each individual life insurance applicant by applying machine learning methods on large dataset. The main objective was to make the application process quicker and less labor intensive which can greatly impact the public perception of the industry. The results will help to better understand the predictive power of the data points in the existing assessment, enabling us to significantly streamline the process. Key Accomplishments:

• Performed Exploratory Data Analysis using Python. Also involved in generating various graphs and charts for analyzing the data using Python Libraries.

• Implemented techniques like forward selection, backward elimination and stepwise approach for selection of most significant features. Used Python Pandas and Scikit-Learn to preprocess the data, including data imputation, outlier detection, label encoding, feature scaling, resampling, and feature engineering to avoid multicollinearity issue.

• Utilized powerful models like Logistic Regression, Linear Regression and Random Forest.

• Participated in all phases of data mining, data collection, data cleaning, developing models, validation and visualization and performed Gap analysis.

• Worked on development of SQL and stored procedures for normalization and denormalization in MySQL.

• Demonstrated experience in the design and implementation of Statistical models, Predictive models, enterprise data model, metadata solution and data life cycle management in both RDBMS, Big Data environments.

• Used Tableau to create detail level summary reports and dashboards to technical and business stakeholders, by using KPI's and visualized trend analysis.

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Data Scientist

• Performed Data Cleaning, features scaling, features engineering, model building using pandas NumPy, Scikit-Learn and keras packages in python.

• Involved working on different data transformation and validation techniques like Dimensionality reduction using Principal Component Analysis (PCA) and Factor Analysis, testing and validation using ROC plot, K- fold cross validation for statistical significance testing.

• Optimized the performance of existing T-SQL queries as per new business logic utilizing indexing strategies as well as re-structuring the code per best practices.

• Configured MySQL Database to store metadata.

• Created effective reports using visualizations such as Stacked Bar chart, Clustered Column Chart, Waterfall Chart, Gauge, Pie Chart, Tree map etc. in POWER BI.

• Build SQL queries for performing various CRUD operations like create, update, read and delete.

• Worked closely with risk teams to find the default users and generated reports grouped by account transactions using Microsoft Excel.

• Involved in data cleansing to remove unnecessary columns eliminate redundant and inconsistent data by using SSIS transformations.

• Extensively used Toad utility for executing SQL scripts and worked on SQL for enhancing the performance of the conversion mapping.

Marlabs Inc, NJ

Mar 2019 – Aug 2019

Vivma, India

Aug 2014 – July 2017

Data Analyst

• Worked on development of data warehouse, Data Lake and ETL systems using relational and non-relational tools like SQL, No SQL.

• Participated in all phases of datamining; data collection, data cleaning, developing models, validation, visualization and performed Gap analysis.

• Design and deploy rich Graphic visualizations with Drill Down and Drop-down menu option and Parameterized using PowerBI.

• Generated comprehensive analytical reports by running SQL Queries against current databases to conduct data analysis.

• Created and designed stable and reliable databases, according to company’s needs.

• Converted various SQL statements into stored procedures thereby reducing the number of database accesses.

• Develop T-SQL procedures, functions and processes using specifications from business analysts and company subject matter experts.

• Designed and implemented basic SQL queries for Data Report and Data Validation.

• Developed database schemas, tables and dictionaries.

• Optimized the performance of existing T-SQL queries as per new business logic utilizing indexing strategies as well as re-structuring the code per best practices. Lamda, India

July 2011 – June 2014

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