This contains detailed steps and stages of developing and delivering the project including timelines. You will learn how to prepare data for analysis, perform simple statistical analysis, create meaningful data visualizations, predict future trends from data, and more! Developed and designed automation framework using Python and Shell scripting. Claims, such as claim settlement duration, number of claims that are filed and denied. Environment: Python, Pandas, Django, Flask, XML, HTML, DHTML, CSS, Angular JS, Java script, Windows. Standardised the data with the help of PROC STANDARD. Environment: Spark, Hadoop, AWS, SAS Enterprise Guide, SAS/MACROS, SAS/ACCESS, SAS/STAT, SAS/SQL, ORACLE, MS-OFFICE, Python (scikit-learn, pandas, Numpy), Machine Learning (logistic regression, XGboost), Gradient Descent algorithm, Bayesian optimization, Tableau. Worked on Java based connectivity of client requirement on JDBC connection. Involved in peer code reviews and performed integration testing of the modules. Running SQL scripts, creating indexes, stored procedures for data analysis. Highly efficient Data Scientist/Data Analyst with 6+ years of experience in Data Analysis, Machine Learning, Data mining with large data sets of Structured and Unstructured data, Data Acquisition, Data Validation, Predictive modeling, Data Visualization, Web Scraping. Used Ajax and JQuery for transmitting JSON data objects between frontend and controllers. Developed the required XML Schema documents and implemented the framework for parsing XML documents. Developed visualizations and dashboards using ggplot, Tableau. Built application logic using Python 2.7. Used Spark and SparkSQL for data integrations, manipulations.Worked on a POC for creating a docker image on azure to run the model. Wrote the data validation SAS codes with the help of Univariate, Frequency procedures. GitHub is where people build software. The data that is obtained for predicting the churn is classified in the following categories. Built models using techniques like Regression, Tree based ensemble methods, Time Series forecasting, KNN, Clustering and Isolation Forest methods. Tasked with migrating the django database from MySQL to PostgreSQL. Used JIRA for bug tracking and issue tracking. Variable selection was done by making use of R-square and VIF values. Built multifunction readmission reports using. Coordinate with data scientists and senior technical staff to identify client's needs and document assumptions. No coding experience required. Part of team implementing REST API’s in Python using micro-framework like Flask with SQLAlchemy in the backend for management of data center resources on which OpenStack would be deployed. SVMs, Decision trees for classification of groups and analyzing most significant variables such as FTE, Waiting times of purchase orders and Capacities available and applied process improvement techniques. Good Knowledge in Proof of Concepts (PoC's), gap analysis and gathered necessary data for analysis from different sources, prepared data for data exploration using data munging. Generating various capacity planning reports (graphical) using Python packages like Numpy, matplotlib. EDUCATION. Developed monitoring and notification tools using Python. Tailor it to a job offer. DATA ANALYST RESUME TEMPLATE (TEXT FORMAT) PROFILE. Built REST APIs to easily add new analytics or issuers into the model. Sentiment scores from past surveys are captured in the latest and average note attitude score fields. Data Scientist with strong math background and 3+ years of experience using predictive modeling, data processing, and data mining algorithms to solve challenging business problems. Developed the project in Linux environment. The model merges the daily data with the historical data and applies various quantitative algorithms to check the best fit for the day. Experienced in installing, configuring, modifying, testing and deploying applications with Apache. Developed various algorithms for generating several data patterns. Programmed a utility in Python that used multiple packages (scipy, numpy, pandas). Extracted data from HDFS and prepared data for exploratory analysis using data munging. Extensive experience in Text Analytics, generating data visualizations using R, Python and creating dashboards using tools like Tableau. Extensive experience in Data Visualization including producing tables, graphs, listings using various procedures and tools such as Tableau. Write Python scripts to parse JSON documents and load the data in database. Data Analyst Intern, Relishly, Mountain View April 2015 – Present Used Agile methodology and SCRUM process for project developing. 2,775 Data Analyst Python jobs available on Indeed.com. Involved in preparation & design of technical documents like Bus Matrix Document, PPDM Model, and LDM & PDM. Proficient in managing entire data science project life cycle and actively involved in all the phases of project life cycle including data acquisition, data cleaning, data engineering, features scaling, features engineering, statistical modeling (decision trees, regression models,clustering), dimensionality reduction using Principal Component Analysis and Factor Analysis, testing and validation using ROC plot, K - fold cross-validation and data visualization. Summary : 10 years of experience as a Data Analyst skilled in recording, interpreting and analyzing data in a fast-paced environment.Proven knowledge in expanding existing data collection and data delivery platforms. Used IMAT to connect the hospital data and execute the code. Used Git 2.x for version control with Data Engineer team and Data Scientists colleagues. Managed datasets using Panda data frames and MySQL, queried MYSQL database queries from python using Python-MySQL connector and MYSQLdb package to retrieve information. Responsible for debugging the project monitored on JIRA (Agile). We’ve analyzed countless applications in order to develop a data analyst resume that will land you more interviews. Tackled highly imbalanced Fraud dataset using undersampling with ensemble methods, oversampling and cost sensitive algorithms. Developed shopping cart for Library and integrated web services to access the payment (E-commerce). Used python APIs for extracting daily data from multiple vendors. Environment: R 3.0, Erwin 9.5, Tableau 8.0, MDM, QlikView, ML Lib, PL/SQL, HDFS, Teradata 14.1, JSON, HADOOP (HDFS), MapReduce, PIG, Spark, R Studio, MAHOUT, JAVA, HIVE, AWS. Environment: SQL Server 2012, Jupyter, R 3.1.2, Python, MATLAB, SSRS, SSIS, SSAS, MongoDB, HBase, HDFS, Hive, Pig, Microsoft office, SQL Server Management Studio, Business Intelligence Development Studio, MS Access. Skilled in using collections in Python for manipulating and looping through different user defined objects. 7 years of experience as a Web Application Developer and Software Engineer using Python, Java, C++. On a typical day, a data analyst might use SQL skills to pull data from a company database, use programming skills to analyze that data, and then use communication skills to report their results to a larger audience. The majority of companies require a resume in order to apply to any of their open jobs, and a resume is often the first layer of the process in getting past the “Gatekeeper” — the recruiter or hiring manager. Developed entire frontend and backend modules using Python on Django Web Framework. Responsible for building data analysis infrastructure to collect, analyze, and visualize data. Implemented web applications in Flask and spring frameworks following MVC architecture. Structuring the Data Marts to store and organize the customer's data. Designed and developed data management system using MySQL. Worked on Business forecasting, segmentation analysis and Data mining and prepared management reports defining the problem; documenting the analysis and recommending courses of action to determine the best outcomes. Performed Data Enrichment jobs to deal missing value, to normalize data, and to select features. Built models using Statistical techniques like Bayesian HMM and Machine Learning classification models like XG Boost, SVM, and Random Forest. Developed Wrapper in Python for instantiating multi-threaded application. Implemented monitoring and established best practices around using elastic search. Points to remember include: Use information in your resume that matches the job description. Love this resume? Good knowledge of HadoopArchitecture and various components such as HDFS, Job Tracker, Task Tracker, Name Node, Data Node, Secondary Name Node, and MapReduce concepts. Also measured the KPIs at MoM (Month on Month), QoQ (Quarter on Quarter) and YoY (Year on Year) with respect to pre-promo-post. And it also pays well. Participated in features engineering such as feature creating, feature scaling and One-Hot encoding with Scikit-learn. Now before you wonder where this article is heading, let me give you the reason of writing this article. Hierarchical, K-means with help of Scikit and Scipy. What to Write in a Data Analyst Resume Skills Section. A Business Data Analyst translates numbers into a written Data, normally the sales, market research, cost and the logistics of any business are measured in numerical values, hence it is the job of a Data Analyst to convert these figures into data and help the management in making better decisions. Used Python scripts to update content in the database and manipulate files. Implemented machine learning model (logistic regression, XGboost) with Python Scikit- learn. Automate different workflows, which are initiated manually with Python scripts and Unix shell scripting. Hands on experience with big data tools like Hadoop, Spark, Hive, Pig, PySpark, Spark SQL,PySpark Hands on experience in implementing LDA, Naive Bayes and skilled in Random Forests, Decision Trees, Linear and Logistic Regression, SVM, Clustering, neural networks, Principle Component Analysis. Perform troubleshooting, fixed and deployed many Python bug fixes of the two main applications that were a main source of data for both customers and internal customer service team. Experienced in developing web-based applications using Python, Django, C++, XML, CSS, HTML, JavaScript, Angular JS and JQuery. Expertise in transforming business requirements into analytical models, designing algorithms, building models, developing data mining and reporting solutions that scale across a massive volume of structured and unstructured data. 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