Data Analyst

KRUTIKA DESHPANDE

Boston, MA- ***** 857-***-****

*********.**@*****.***.*** linkedin.com/in/krutikadeshpande

Machine Learning Engineer Data Analyst Business Intelligence Analyst

Diligent technical professional passionate about cutting-edge technology and solving real-world problems, with experience in analyzing complex data, discovering meaningful patterns and furnishing insights, business intelligence needed for effective decision making.

Data & Quantitative Analysis / Machine Learning Algorithms / Predictive Modeling / Data-Driven Personalization

Data Mining & Visualizations / Troubleshooting & Issue Resolution / Business Intelligence / Requirement Analysis

EDUCATION

Master of Science in Information Systems Northeastern University, Boston, MA

Bachelor of Engineering in Electronics University of Mumbai, India

TECHNICAL SKILLS

Technical Skills:

Python (NumPy, SciPy, Pandas, scikit-learn, pyplot), R (caret, dplyr,e1071,glmnet,ggplot), PL/SQL, Java

Databases:

Oracle 11g, SQL Server 2015, PostgreSQL, MySQL

Visualization:

Tableau, Power BI, QlikSense, QlikView, Google Analytics, ServiceNow SURF

Tools:

Hadoop MapReduce, Rstudio, Jupyter Notebook, Amazon Web Services (AWS), Toad for Data Analysts, ServiceNow, GitHub, NetBeans, SQL Server Management Studio, Talend, Azure Machine Learning Studio, Docker, SQL Server Integration Service, Weka, Orange

Other Skills:

Apache Spark, Apache Hadoop 2.7.3, Linux, Machine Learning, Deep Learning, Supervised and Unsupervised algorithms, Natural Language Processing, Statistics, SQL Optimization, UML, JIRA, Bugzilla, Agile

PROFESSIONAL EXPERIENCE

Data Analyst Business Analyst Intern

ServiceNow, Boston, MA, USA Aug 2017 – Dec 2017

Oversaw ongoing analyses of active employee utilization using Tableau and SURF (ServiceNow Analytics Tool) in an agile environment. Extracted data from multiple sources, conducted root cause analysis, forecasted impact and documented trends.

Spearheaded the company’s SURF platform for predictive analytics. Saved more than 85% in time and effort by automating processes involving data extraction from database and analysis in Excel.

Provided internal business stakeholders with analytics and decision-support tools, proposed solutions meetings the defined specifications and needs. Computed human resources metrics and KPIs indicating 62% productivity increase and developed quarterly prediction reports.

Software Engineer

Cognizant Technology Solutions Pvt Ltd, India Sep 2014 – Jul 2016

Performed quality assurance, system integration and user acceptance testing facilitating on-time ‘go-live’ of the inventory implementation for up to 20,000 global users.

Collaborated on a Performance Improvement Tool to monitor and record time-savings following process automation. Documented the test plan and test strategy for the releases.

Investigated a failure in the inventory system, and identified the root-cause as a rule conflict between the main distributor and the cable splitter. Implemented solutions involving adding an additional testing plan to the deliverables.

Mastered the Waterfall model collaborating with internal stakeholders to isolate and resolve bug fixes using Bugzilla. Demonstrated subject matter expertise in products with strong communication and problem-solving skills.

ACADEMIC PROJECTS

Deep Learning – Human Activity Recognition

Built a classification model using Decision Tree, K-Neighbors, SVC, and GaussianNB. Employed the main steps of the machine-learning algorithm including predictions, gradient descent, and derivative computation for backward propagation.

Developed a recurrent neural network(RNN) or sequence identification and activity classification, using Keras, which involved sequential modeling with Gated Recurrent Unit layer, dense layer, and Adam optimization.

Performed structured streaming for feature extraction in Apache Spark and developed long short-term network(LSTM) layers in Tensor flow for learning long-term dependencies.

Developed an Android application to predict the real-time human activities deploying the designed model and created web service to remotely monitor the human activities for medical, security and surveillance.

Machine Learning – Lending Loan Club

Executed web scrapping, parsing files, missing data analysis, feature engineering and handling observable anomalies for entire Accepted & Rejected Dataset and automated all the tasks using data pipeline in Python.

Designed an entire flow of machine learning algorithms to predict the loan status based on user input attributes.

Implemented Classification and Prediction using supervised techniques like SVM, Random Forest, Neural Network, Logistic Regression, Linear Regression, and KNN. Performed Clustering using unsupervised techniques like K-Means and Hierarchical.

Natural Language Processing – Google Mini Reviews

Executed web scrapping of 5000 customer reviews of Google Mini from BestBuy based on the HTML tags. Analyzed the features, missing data and handled observable anomalies using data pipeline in Python.

Tokenized the reviews and removed stopwords using nltk. Extracted subjective emotions and feelings from the reviews. Distinguished the sentiment of the reviews as either positive or negative comparing the words with Bing Lexicon.

Implemented Naïve Bayes Classifier for text classification predicting the sentiment of the reviews with 86% accuracy.

ETL and Business Intelligence – Contoso Data Warehouse

Extracted data from relational databases (SQL Server, Oracle 11g, PostgreSQL, and MySQL), flat files, and XML files through ODBC and OLE DB connections. Identified the business process, the granularity of the fact data and striped out dimensions to design a star schema dimensional data model maintaining the 5C’s (consistent, clean, current, comprehensive, conformed).

Transformed the data from the source into the staging area in Talend and SQL Server Integration Services handling the slowly changing dimensions and data integrity. Loaded the data in final appropriate format into the data warehouse.

Analyzed sales trends in Tableau to identify markets to improve existing sales of products. Forecasted sales in QlikSense and Power BI monitoring the factors impacting the sales and revenue.

Hadoop - Crimes in Chicago

Mapped crime data with police stations and established a pipeline using concepts of MapReduce chaining. Automated an analysis which eliminated the need to have jobs run simultaneously. Executed summarization, organization, filtering, and join patterns on 2GB data.

SQL Modeling – Target Retail Store Management

Designed a database model for Target Retail Store Inventory department. Developed the Entity-Relationship diagram (ERD) in Toad Data Modeler illustrating the logical structure of the database.

Involved extensive data validation, maintained the referential integrity and solved data quality issues writing complex SQL queries. Applied stored procedures and triggers to understand customer behavior and framed insights based on their tendency.

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