Used JIRA for bug tracking and issue tracking. Data Analyst with 5+ years of experience skilled in recording, interpreting and analyzing data. No coding experience required. If your resume has relevant Data Analyst Resume Keywords that match the job description, only then ATS will pass your resume to the next level. Used Python to preprocess data and attempt to find insights. Generated Python Django Forms to record data of online users. Participated in Data Acquisition with Data Engineer team to extract historical and real-time data by using Hadoop MapReduce and HDFS. What to Write in a Data Analyst Resume Skills Section. Developed various algorithms for generating several data patterns. Added several options to the application to choose particular algorithm for data and address generation. Developed UI of the report based on the business requirement. Structuring the Data Marts to store and organize the customer's data. Designed and developed the UI of the website using HTML, XHTML, AJAX, CSS and JavaScript. Built the model in R and model deployment using Python. Completed market analysis, resulting in a 21% increase in sales. Excellent analytical and problem solving skills and ability to work on own besides being a valuable and contributing team player. Experience in using collections in Python for manipulating and looping through different user defined objects. Data elements validation using exploratory data analysis (univariate, bivariate, multivariate analysis). Luckily, that’s not entirely true in data science. Utilized Sqoop to ingest real-time data. Analyzed performance test requirements and developed test plans and have done debugging to understand test objective requirements. 2.3 Uber Data Analysis in R. Check the complete implementation of Data Science Project with Source Code – Uber Data Analysis Project in R. This is a data visualization project with ggplot2 where we’ll use R and its libraries and analyze various parameters like trips by the hours in … Used Spark and SparkSQL for data integrations, manipulations.Worked on a POC for creating a docker image on azure to run the model. Extracted data from HDFS and prepared data for exploratory analysis using data munging. 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. Worked with Machine learning algorithms like Linear Regressions (linear, logistic etc.) Implemented monitoring and established best practices around using elastic search. 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. Experience in designing stunning visualizations using Tableau software and publishing and presenting dashboards, Storyline on web and desktop platforms. Built various graphs for business decision making using Pythonmatplotlib library. Designed and developed data management system using MySQL. According to Glassdoor, “Data Scientist” tops the list of the best jobs in 2020, with a median base salary of $110,000.. It’s not just that they pay well, data scientist positions are in high demand too - 6.5 times as many data scientist positions were posted on LinkedIn in 2018 than in 2012. Performed 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. Worked on updating the existing clip board to have the new features as per the client requirements. Used IMAT to connect the hospital data and execute the code. Leverage tools like R, PHP, Python, Hadoop & SQL to drive efficient analytics 19 Risk Data Sourcing Business Analyst Resume Examples & Samples. 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. 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. Developed Wrapper in Python for instantiating multi-threaded application. And utilized SAS for developing Pareto Chart for identifying highly impacting categories in modules to find the work force distribution and created various data visualization charts. Developed entire frontend and backend modules using Python on Django Web Framework. Measured the ROI based on the differences pre-promo-post KPIs. Involved in Unit testing and Integration testing. GitHub is where people build software. The data that is obtained for predicting the churn is classified in the following categories. Experience with continuous integration and automation using Jenkins. Experienced in developing Web Services with Python programming language. Understanding of Python best Practices (PEP-8). P.O.W.E.R Resume System: Proven system to get job interviews. To put it simply, a data analyst is someone who uses technical skills to analyze data and report insights. Built REST APIs to easily add new analytics or issuers into the model. Adept in statistical programming languages like R and Python including Big Data technologies like Hadoop, Hive. Worked on Clustering and factor analysis for classification of data using machine learning algorithms. Used Git 2.x for version control with Data Engineer team and Data Scientists colleagues. Angular.js is used to build efficient backend for client web application. Worked and extracted data from various database sources like Oracle, SQL Server, DB2, regularly accessing JIRA tool and other internal issue trackers for the Project development. Now before you wonder where this article is heading, let me give you the reason of writing this article. Implemented machine learning model (logistic regression, XGboost) with Python Scikit- learn. Normalized the data that is loaded into the, Designed and Developed User Interface using front-end technologies like. Developed tools using Python, Shell scripting, XML to automate some of the menial tasks. Environment: Java, Servlets, JDBC, HTML, CSS, JavaScript, JSON, XML, PL/SQL, SQL, web services, JUNIT. Worked extensively with data governance team to maintain data models, Metadata and dictionaries. Missing value treatment, outlier capping and anomalies treatment using statistical methods. Complaints, such as number of open and closed complaints. Adept and deep understanding of Statistical modeling, Multivariate Analysis, model testing, problem analysis, model comparison, and validation. Responsible for building data analysis infrastructure to collect, analyze, and visualize data. Explain how you learned your skills Maintenance in the testing team for System testing/Integration/UAT. Monash University, Clayton Campus. Involved in preparation & design of technical documents like Bus Matrix Document, PPDM Model, and LDM & PDM. Expertise in Service Oriented Architecture (SOA) and its related technologies like Web Services, BPEL, WSDLs, SOAP1.1, XML, XSD, XSLT etc. Communicated and presented default customers profiles along with reports using Python and Tableau, analytical results and strategic implications to senior management for strategic decision making Developed scripts in Python to automate the customer query addressable system using python which decreased the time for solving the query of the customer by 45% * Collaborated with other functional teams across the Risk and Non-Risk groups to use standard methodologies and ensure a positive customer experience throughout the customer journey. Gained expertise in Data Visualization using matplotlib, Bokeh and Plotly. Extensive experience in Text Analytics, generating data visualizations using R, Python and creating dashboards using tools like Tableau. Captures the changes for each market to create a daily email alert to the client to help make better investment decisions. Maintained the versions using GIT and sending the release notes for each release. Environment: Python, MySQL, Django, Flask, PHP, XML, HTML, DHTML, CSS, Angular JS, Java script, Windows, Linux. Provided GUI utilizing PyQt for the end user to create, modify and view reports based on client data. Resume building is very tricky. Demographic data, such as age, gender, education, marital status, employment status, income, home ownership status, and retirement plan. Claims, such as claim settlement duration, number of claims that are filed and denied. Updated and manipulated content and files by using python scripts. Worked on predictive analytics use-cases using Python language. Built the model on Azure platform using Python and Spark for the model development and Dash by plotly for visualizations. Typical responsibilities included in a Python Developer resume examples are writing code, implementing Python applications, ensuring data security and protection, and identifying data storage solutions. 4890 tuples using bar charts, box plots and histograms. Aug 2016. EDUCATION. Summarising the data at customer level by joining the datasets of customer transaction, dimension and from 3rd party sources. Worked on Python OpenStack APIs and used NumPy for Numerical analysis. Sentiment scores from past surveys are captured in the latest and average note attitude score fields. Experience with Data Analytics, Data Reporting, Ad-hoc Reporting, Graphs, Scales, PivotTables and OLAP reporting. Built and analyzed datasets using R, SAS, Matlab and Python (in decreasing order of usage). Environment: Python 2.4, CSS, HTML, BOOTSTRAP, JavaScript, JQuery, AJAX, MYSQL, Linux, Heroku, GIT, flask and python libraries such as NumPy, SQL Alchemy, MySQL DB, Automation framework, Jenkin. Supported MapReduce Programs running on the cluster. Built application logic using Python 2.7. Created and published multiple dashboards and reports using Tableau server. Analyzed the partitioned and bucketed data and compute various metrics for reporting. Involved in writing test cases using JUNIT. Programmed a utility in Python that used multiple packages (scipy, numpy, pandas). Optimized algorithm with stochastic gradient descent algorithm Fine-tuned the algorithm parameter with manual tuning and automated tuning such as Bayesian Optimization. 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. What is a Data Analyst? 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. Extensive experience in Data Visualization including producing tables, graphs, listings using various procedures and tools such as Tableau. Participated in all phases of datamining; datacollection, datacleaning, developingmodels, validation, visualization and performed Gapanalysis. Developed test plans and procedures from the requirement and specification documents. 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. Used Python to place data into JSON files for testing Django Websites. Writing a resume for data science job applications is rarely a fun task, but it is a necessary evil. Performed analysis on businesses as well as users data and outlined the analysis using interactive visualizations in python. Worked on development of SQL and stored procedures on MYSQL. Developed UI of the report based on the business requirement; Generated the readmission reports for the hospitals of Delaware and Maryland. Experience object oriented programming (OOP) concepts using Python, Django and Linux. A data analyst uses Tableau, NOT a data scientist or machine learning engineer. DATA ANALYST RESUME TEMPLATE (TEXT FORMAT) PROFILE. Involved in capturing the requirements for serial functional interface and other software requirements specification document. Developed Hive queries that compared new incoming data against historic data. Designed and created backend data access modules using PL/SQL stored procedures and Oracle. Flinders University, Adelaide, SA. Used the Django Framework to develop the application. Created Servlets and Beans to implement Business Logic. Used many regular expressions in order to match the pattern with the existing one. You’ll learn to manipulate and prepare data for analysis, and create visualizations for data exploration. Developed a technical brief based on the business brief. Used Ajax and JQuery for transmitting JSON data objects between frontend and controllers. I had to assist the Flash developer send the correct data via query strings. Extensively used Python's multiple data science packages like Pandas, NumPy, matplotlib, Seaborn, SciPy, Scikit-learn and NLTK. Developed views and templates with Python and Django's view controller and templating language to create a user-friendly website interface. 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. Improved fraud prediction performance by using random forest and gradient boosting for feature selection with Python Scikit-learn. The model merges the daily data with the historical data and applies various quantitative algorithms to check the best fit for the day. Worked on Java based connectivity of client requirement on JDBC connection. Maintained PL/SQL objects like packages, triggers, procedures etc. Responsibilities: Built multifunction readmission reports using python pandas and Django frame work; Used IMAT to connect the hospital data and execute the code. Utilize SQL, Excel and several Marketing/Web Analytics tools (Google Analytics, Bing Ads, AdWords, AdSense, Criteo, Smartly, SurveyMonkey, and Mailchimp) in order to complete business & marketing analysis and assessment. These tips that we shared should help you build a solid business data analyst resume. Automate different workflows, which are initiated manually with Python scripts and Unix shell scripting. 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. Time Series Analysis •Performed data mining, data cleaning & explored data visualization techniques on a variety of data stored in spreadsheets and text files using R and plotting the same using ggplot2 function •Sufficient exposure to designing and developing Tableau reports and dashboards for data visualization using R & Tableau The job of a Data Analyst is a crucial one for the company. Experience and Technical proficiency in Designing, Data Modeling Online Applications, Solution Lead for Architecting Data Warehouse/Business Intelligence Applications. Environment: Python 2.6/2.7, JavaScript, Django Framework 1.3, CSS, SQL, MySQL, LAMP, JQuery, Adobe Dreamweaver, Apache web server. Experience in python, Jupyter, Scientific computing stack (numpy, scipy, pandasand matplotlib). Conducted research using focus groups on 3 different products … 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. Involved in Python open source community and passionate about deep reinforcement learning. Involved in developing the UI pages using HTML, DHTML, CSS, JavaScript, JSON, jQuery, Ajax. 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