- Process oriented 8 years of professional experience in Data Analyst/ Data Analytics. Mainly, IT industry and Expertise in using Python, R, Data analyzing, Big data Technologies, Data Mining Techniques. Demonstrated strong communication skills in collaboration with business partners throughout the project lifecycle . Flexible thinker and team player that is dedicated to supporting quality improvement initiatives of the organization .
- Experience in transforming raw data into actionable strategic knowledge to gain insight into business processes, and thereby guide and help businesses in their decision - making and run efficiently.
- Wide array of experiences in interpreting and analyzing data using statistical techniques and systems.
- Strong numerical, interpretative, analytical and diagnostic s Skills.
- Hands-on experience in data design and analysis using Machine Learning Technics and modules .
- In depth understanding/knowledge of Hadoop Architecture and various components such as HDFS, HIVE MapReduce and YARN concepts.
- Extensive Knowledge in implementation of machine learning modules in Python.
- Extensive experience in in-depth data analysis on different data bases and structures. Strong knowledge in writing SQL Queries, sub-queries, and joins.
- Skilled in providing analytic support including data importing, data wrangling and data visualization.
- Expert in Applying Advance MS excel and Adept in MS Excel with proficiency in Vlookups, Pivot Tables.
- Expert in Visualizing, Conceptualizing, Specifying and Documenting the Business Architecture artifacts and Use case diagrams using MS Visio.
- Experience in designing stunning visualizations using Tableau software and publishing and presenting dashboards on web and desktop platforms.
- Proficient in trouble shooting various applications specific or any Data Analysis code in PYTHON/R.
- Excellent communication, team oriented and interpersonal skills, Quick Learner, Exceptional Team Player and have the ability to work independently as well.
Relational Database: Oracle 11g, SQL Server 2008, MySQL, DB2,, HSQLDB.
Programming: Python, R, SQL, Hive.
Operating System: Linux, Windows XP/7/8/10, Mac
Business Intelligence Tools: Tableau 9.1, MS Power BI, MS Excel - Analytical Solver, SSRS.
Statistics: Mean, Median, Mode, Data Distributions, Standard Deviation and Variance, Hypothesis Testing (p-values) and Test for significance- t-test.
Frameworks: Apache Hadoop, Hive, Apache Spark.
Machine Learning: Feature Selection Supervised and Unsupervised Learning, Correlation Analysis, Linear Regression, Multiple Linear Regression, Logistics Regression, Clustering, Classification, Decision Tree, Support Vector Machines (SVM), Naive Bayes, K- Nearest Neighbors (KNN), Clustering, K-Means Clustering, Random Forest
Development tool: Eclipse, NetBeans, Visual Studio, Jupyter notebook, Spyder, Anaconda.
Confidential, Minneapolis, MN
- Help users make effective merchandise planning and inventory planning decisions.
- Define and build Demand Forecasting insights and measurement product in service of its customers in supply-chain and merchandising
- Responsible for monitoring Demand forecast performance, identify forecast exceptions, root-cause drivers of defects and execute corrections to the forecasts.
- Primary point of contact for users and customers of DFE.
- Drive Demand Forecast Engine Operations reviews with Business partner.
- Share recent Demand forecast performance with business partners
- Diagnose reasons for product feature gaps (data, model etc.) and hold development teams responsible
- Responds to product feature related queries from business partners/users
- Own and execute forecast exception management process, analyze forecast exceptions and make manual/programmatic corrections to forecast defects.
- Educate new users about Demand Forecast Engine product features and respond to queries
- Part of the Product Management team for an Enterprise Demand Forecasting Engine.
- Liaison with Business Partners, Data Scientists and Engineers on an on-going basis to develop and improve the product.
- Co-ordinate with Business Partners (Supply Chain) to get consumer feedback and discuss resolution plan and updates
- Monitor the product performance systematically to identify issues and share feedback with the development team
- Analyze trends in categories, stores, distribution centers across service level, forecast accuracy metrics to identify product improvement opportunities
- Plan and execute short term issue resolution strategies in co-ordination with the measurement team
- Member of the Operations team responsible for operations decisions across all stores for the internal demand forecasting product and ensuring forecast quality meets goal across replenishment and purchasing use-cases.
- Partner with consumer product owners, inventory analysts, and inventory management operations team to understand opportunities and relay back with senior leadership team.
- Support decisioning on go/no-go on inventory planning expansion
- Identify and raise forecast quality issues/ bugs with the development team
- Developing exception reporting & performance visualization tools
- Building analytical products for improving Supply chain operations.
- Advanced/intermediate experience in any of these querying languages like SQL, HIVEQL
- Proficient in BI tools like Tableau, Domo, MicroStrategy etc.
- Excellent stakeholder's communication - written, verbal and telephonic
- Quick analysis and summarize results on MS Excel, PowerPoint.
- Big Data Analysis using analytical platforms- R (Packages) or Python packages.
- Statistical testing and measurement, forecasting validations.
- Working in an agile (scrum or kanban) product development model.
- Applied Metrics like ALPHA, BIAS, MAPE, WIN for evaluating the model under forecast/Over Forecast.
Confidential, Richmond, VA
- Wrote Python Script for consolidating the Excel Data into one for the PHRBR Review by the management.
- Wrote Python Script for validating the Accounts with Screenshots, and Accounts missing screenshots for business review.
- Performed Address Swap Analysis between the Capstone, AIS, and TSYS data using Databricks, and Snowflake, to identify the accounts which had addresses swapped incorrectly between primary and the business.
- Performed Data Analysis and Wrote complex SQL Scripts for the Accounts with Money Laundering Risk, gap analysis between the Account Closure Date and Actual Closure.
- Identifying the customer with high risk, NIAT values, Statements Amounts, Transaction Amounts, Cash Advances, and Credit Limit.
Technologies: DataBricks, Spark SQL, Teradata SQL Assistant, Snowflake, Python
Confidential, Minneapolis, MN
Data Analytics Consultant:
- Visualized the time series data of sales and checked for stationarity using Dickey Fuller test.
- Made the time series data stationary and applied ARIMA model for forecasting sales, this helped in maintaining the inventory as per the sales.
- Built Machine learning model by applying ridge regression, tree-based learners, neural networks to forecast the Inventory Demand.
- Supported in reducing the number of overstocked items and, also increased the number of understocked items.
Environment: MS EXCEL, SQL, Lumira, R Programming, RStudio
Confidential, Saint Paul, MN
Research Data Analyst
- Analyzed and interpreted datasets in RStudio generated by course evaluation surveys in Qualtrics to build insightful Data Visualizations.
- Worked on Tableau Desktop and created dashboards, graphs and Summaries, calculated expressions.
- Applied Tableau features including calculated fields, parameters, table calculations, data blending, dashboard, and Pareto charting, advanced calculations, demographic and geographic fields for creating visualizations.
- Worked on Tableau Action Filters, LOD Expressions and Drill Down Features.
Environment: R, Oracle DB 11g, SQL-Server, Microsoft Excel, Qualtrics, Tableau