- Over 8 years of experience in supporting business solution software and analyzing business operations. Expert interpersonal communicator with solid and experience in data integration, data mining, predictive modeling, Statistical analytics, data visualization with large data sets of structured and unstructured data, and client relationship management to support organizational objectives.
- Extensive experience in developing predictive systems and implementing efficient algorithms to improve data quality; identifying, evaluating, designing, and performing statistical analyses of gathered data to create analytic metrics and tools.
- Skilled in designing, building, and deploying data analysis systems for large data sets; implementing algorithms to extract information from large data sets; establishing efficient, automated processes for model development, validation, and large - scale data analysis.
- Experience in selecting features, building and optimizing regressors/classifiers using machine learning techniques.
- Strong problem-solving skills with an emphasis on product development; experience working with and creating data architectures; knowledge of a variety of machine learning techniques and algorithms (Logistic Regression, Clustering, Decision tree learning, support vector machines, K-Nearest Neighbors, artificial neural networks, etc.) and their real-world advantages/drawbacks.
- Strong understanding of Data Science Research Methodologies, statistical concepts, data mining techniques and multivariate data visualizations.
- Experience working with Python to automate the operations that are used in data cleaning, data ingestion using Pandas framework. (Numpy, SciPy, Pandas, Matplotlib, Scikit-learn)
- Experience working with R packages, libraries and lexicons for sentiment analysis of text data.
- Experience of de ning key facts and dimensions necessary to support the business requirements along with Data Modeler.
- Ability to educe, define, and document business user requirements. Managing, analyzing and translating requirements and objectives into business/technical requirements based on project scope parameters.
- Strong experience in Requirements elicitation techniques - conducting user interviews, survey creation and Focus Groups, document analysis, JAD sessions and managing the requirements. Expert in user interface designing and creating wire frames, and expert in using tools like MS Project, MS Visio, draw.io, Balsamiq mockup and photoshop.
- Working experience of advanced Microsoft Excel functions, ETL (Extract, Transform and Load) of data into a data warehouse/data mart and Business Intelligence (BI) tools like Microsoft Power BI and Tableau (Data visualization and Analytics).
- Hands on experience in writing queries in SQL to extract, transform and load (ETL) data from large data warehouse systems.
- Extensive experience in diverse and home-grown methodologies such as Agile System Development Life Cycle process, implementing the Rational Unified Process (RUP) in all different phases of SDLC.
- Efficient in MS Project/MS Excel for planning/status reporting/writing test scenarios.
- Built strong relationships with clients and demonstrated commitment to delivery.
- Strong communication, business understanding, critical thinking and analytical skills.
Data Modeling Tools: MS Visio, Lucidcharts, Draw.io
Reqs. Management: Rational RequisitePro, JIRA
Project Management Tools: MS Project, Asana
Analysis/Modeling/Visualization Tools: IBM SPSS Statistics 24, Tableau 10.5, Informatica, Php MyAdmin, RStudio, Jupyter Notebook, PowerBI, NodeXL
Operating Systems: MS Windows NT/98/95/2000, UNIX
Languages: SQL, R, Python
ML: K: Nearest Neighbors, Na ve Bayes, Decision Trees, Regression models, random forests, K-means clustering, Time-series and support vector machines.
Big Data frameworks: Apache Hadoop, Hive and Spark
Database: MySQL 8.0, HDFS
Web services: Amazon EC2
Utility: MS Office Suite, Adobe Photoshop CC 2018, Balsamiq Mockup, Qualtrics Survey
Confidential, Milpitas, CA
- Responsible for data and business system analysis of customizing the SAS collaboration product with involvement through the whole SDLC.
- Applied various machine learning algorithms and statistical modeling like decision trees, regression models, neural networks, SVM, clustering to identify Volume using scikit-learn package in python.
- Conducted data regression analyses of the relationship between product’s module prices and industry trends, achieving a 15% more accurate prediction of pricing than previous years.
- Modernize data streamlining processes, resulting in a 25% redundancy reduction.
- Improved data mining processes, resulting in a 20% decrease in time needed to infer insights from customer data that was used to develop marketing strategies.
- Used predictive analytics such as machine learning and data mining techniques to forecast company sales of new product offerings with a 95% accuracy rate.
- Used Python and SPSS to build models to identify definite patterns and suggest business with possible problems and feasible solutions. Provided feedback on the quality of data including identification of patterns and outliers.
- Mined huge amount of cases from legacy systems to make prediction and pattern recognition using statistical analysis using regression/classification and clustering techniques in Python.
- Used pandas, numpy, seaborn, scipy, matplotlib, scikit-learn, NLTK in Python for implementing various machine learning algorithms.
- Identified dependent and independent variables in customer survey data to perform regression analysis for examining relationship between them that generates actionable business insights.
- Created and used Filters, Quick Filters, Table Calculations and Parameters on Tableau reports.
- Created various views in Tableau like Tree maps, Heat Maps, Scatter plots, Geographic maps, Line chart, Pie charts based on client needs for dynamic interactions with the data produced.
- Performed sentiment analysis on unstructured text data gathered from social media platforms (Twitter, Consumer reviews from G2 Crowd, TrustRadius, GetApp etc.) using R packages, libraries and lexicons for garnering competitive business intelligence.
- Extracted data from various sources like Oracle, XML, Excel and COBOL Flat Files.
- Merged, Cleansed and processed collected data using Excel and Pandas framework.
- Designed, developed and implemented databases running on MySQL 8.0 database server using ‘phpMyAdmin’ web-based client to assist with applicant tracking, inventory, vendor tracking and various other data control needs.
- Designed and implemented basic SQL queries for testing and report/data validation.
- Launched, configured and connected to AWS remote instance (Virtual Machine containing Apache Hadoop framework) on Amazon EC2 to map query performance on large datasets using HiveQL and SparkSQL.
- Gathered the data and the objective of database as per the business requirement.
- Made list of Entity and built the data base Schema.
- Identified the different type of keys such as Primary Key, Foreign Key etc. that are useful in building relations between the tables.
- Created Entity relationship diagrams using Draw.io, MS Visio, Lucid charts and data dictionary in Excel and MS Word templates.
- Created Relationships among tables that might be of different type such as one-one relation, one-many relation, many-one relation, many-many relation.
- Normalized the data with certain rules like obtaining first normal form, second normal form, third normal form.
- Defined and represented Entities, Attributes, various Keys and Joins between the entities using SQL.
- Created design documents like data flow diagrams, process flow charts using MS VISIO and UML.
- Used Excel and PowerPoint on various projects as needed for presentations or summarization of data to provide insight on key business decisions.
- Extracted, discussed, and refined business requirements from business users and SME’s.
- Analyzed and tested interfaces for different modules within the product such as applicant tracker, vendor management, project management, IT asset management etc. Created User Interface mockups.
- Acted as liaison between development team, and Business SMEs to gather data for the standardization of Functional requirements documents and Use cases.
- Collected, cleansed and provided modeling and analyses of structured and unstructured data for major business initiatives. (R, Python)
- Manipulated and processed large data using Excel, Access and SQL.
- Responsible for loading, extracting and validation of client data.
- Coordinated with the front-end design team to provide them with the necessary stored procedures and packages and the necessary insight into the data.
- Participated in requirements definition, analysis and the design of logical and physical data models.
- Created multiple Visualization reports/dashboards using Dual Axes charts, Histograms, Bubble chart, Bar chart, Line chart, Tree map, Box and Whisker Plot, Stacked Bar etc.,
- Generated Tableau Dashboard with quick/context/global filters, parameters and calculated fields on Tableau reports.
- Created Tableau Dashboards with interactive views, trends and drill downs along with user level security.
- Used Pandas DataFrame for structuring, cleansing and manipulation of data.
- Published Tableau Workbooks by creating user filters so that only appropriate teams can view it
- Designed and developed various analytical reports from multiple data sources by blending data on a single worksheet in Tableau Desktop and created Tree Map, Heat maps and background maps.
- Involved in generating dual-axis bar chart, Pie chart and Bubble chart with multiple measures and data blending in case of merging various sources.
- Conducted work ow, process diagram, and gap analysis to derive requirements for existing systems enhancements. Responsible for developing monthly reports using Tableau.
- Conducted key analytics (data sourcing, analysis, testing) required to inform strategic recommendations (e.g., competitor benchmarking, market assessment and financial modeling.
- Performed data mining on the client data through various clustering techniques using SPSS with an intention to identify structures within the data or homogeneous groups of data based on variable types.
- Analyzed data points and trend and generated reports for each business region.
- Segmented this clustered data and built a predictive model for forecasting region’s performance and potential markets for revenue generation and investment.
- Developed visualizations of the forecasted trend for profiling of data through R and Tableau.
- Used SPSS to mine, alter, code and retrieve data from a variety of sources and perform statistical analysis on them.
- Coordinated with customers, support, sales and development teams, resolved issues.
- Organized and facilitated sprint planning, daily stand-up meetings, Scrum of Scrum, Sprint review, Sprint retrospectives, and other Scrum-related meetings. Ensured high quality data collection maintaining the integrity of the data.
- Gathered data about consumers, competitors, and market conditions through surveys, questionnaires, focus groups and opinion polls, and converted complex data and findings into understandable tables, graphs, and written reports using data visualization and storytelling.
- Conducted market research and deployed successful marketing campaigns. Maintained robust communication channels among internal and external stakeholders supporting brand recognition/equity.
- Collected and analyzed data on established and prospective customers, competitors, and marketing channels and advertising opportunities.
- Responsible for extracting, compiling and tracking data for making reports on a weekly & monthly basis using MS Excel.
- Created pivot tables and charts using worksheet Data and external resources, modified pivot tables, sorted items and grouped Data, and refreshed and formatted pivot tables.
- Prepared reports that interpret consumer behavior, market opportunities and conditions, marketing trends and investment levels.
- Copyediting, proofreading and revising communications.
- Creating and delivering press releases, media relation content, thought leadership content and social media content.
- Tracking the health and success of online campaigns using a Google analytics.
- Working closely with marketers to ensure marketing campaigns are properly tagged and tracked.
- Working with product teams to ensure products go to market in a data driven manner.
- Creating marketing presentation and promotional materials.
- Composing and publishing monthly corporate Newsletter.
- Working with advertisers for usable ad submissions on time.
- Researching media coverage and industry trends.
- Identifying and developing communication strategy for marketing campaigns and representing company in Industrial trade fairs.
- Providing communication skill to employees.
- Involving into end to end recruitment process from bagging requirement, sourcing, screening, submitting resumes, interview process, selection, signing contracts to follow-up, maintaining relationship with candidates and managing database.