Data Scientist Resume

PROFILE:

Proficient in Predictive Modeling, Statistical Analysis and Data Mining with experience using statistical programming such as R programming, Python, and Base SAS. Adept in implementing regression analysis, deep learning, neural networks, and advanced ML algorithms such as Random Forest, XGBoost, Gradient Boosting Machine, Linear & Logistic Regression
6+ years of experience in Machine Learning, Quantitative Analysis, Decision Analytics, Big data, MS - SSIS, SSRS, SQL Development, Data Mining, Business Intelligence and Visualization Tools
Expertise to leverage mathematics and applied statistics to design of experiments on structured, and unstructured data.

LEADERSHIP SKILLS:

Spearheaded a technical team of 20 members under Agile environment and delivered Quality IT Services
Officer at Intelligence Analytical Society (IAS - UTD), organized and conducted workshops on SQL, R Programming

TECHNICAL SKILLS:

Programming: R programming, Python, Base SAS, SQL, Java, Unix, C, C++

Statistical Tools: R-Studio, SAS EM, IBM SPSS Modeler, MS SSAS

Big Data Technologies: Hadoop, HDFS, MapReduce, Hive, Pig, Mongo DB, NoSQL

Visualization Tools: Tableau, Crystal Reports, Lumira, D3

WORK EXPERIENCE:

Data Scientist

Confidential

Responsibilities:

Managing Confidential -Innovation Lab’s Data Science Team by leading multiple research and business ideas from various Confidential ’s functional groups.
Designed, Developed and Deployed Tower Climb solution that has three different predictive models for customers.
Architected and Implemented an AI system which predicts network Hardware faults with up to 5% margin for customer Confidential .
This intelligence system helped radio operations personnel to act and correct radio network components.
Developed and Deployed machine learning model to predict Network node down case in advance for customer Entel.
Performed ad-hoc Statistical analysis, and created insights into data to provide business actionable insights; identified trends, and measured performance that addressed network related business problems

Data Scientist

Confidential

Responsibilities:

Developed machine learning algorithms using R, Java, SQL and Visualization Tools to predict potential customers and fallout ratio.
This mitigated the customer’s fallout, improved customer’s satisfaction, increased the client’s revenue and growth in number of users.
Performed statistical data analysis of M&S retail store transaction and developed formal reports that helped stake holders to identify potential areas of lower sales trend, that shields business of £2 million
Created an improved store target and services for M&S retail by doing Statistical Research and Predictive Modeling (Inventory Prediction, Driver Behavior Analysis, Fuel Economy Pattern Analysis, and Auto Massage Engine) using R, Java, SQL and Excel.
Personally responsible for R&D, testing and production cycles of two separate projects in Advanced Analytics Team. This aided to invent a sentiment analysis algorithm that resulted more than 90% accuracy in text mining. This prototype helped to procure 3 multi-national clients.
Conducted Data analysis, created datasets and reports by extensive use of Base SAS - SAS/Macros, SAS/SQL, SAS/Reports
Extensively designed Data mapping, filtering, consolidation, and data transfers between applications using MS SSIS and adept in creating data models, database tables, views, stored procedures using MS-SQL server
Increased data flow transparency by monitoring KPIs, devised value additions, resulting process improvement by 30% ed with ‘Technical Excellence’ by TCS for providing efficient solutions to the business needs.

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