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About Me
- Data scientist with python exp.
- A focused professional with over 12 years of IT experience in software application development, support and maintenance activities in various projects including Data Science, Big Data and Machine Le...pport and maintenance activities in various projects including Data Science, Big Data and Machine Learning Techniques.
- Experienced in building Machine Learning and Deep Learning Models in Statistical R and Python programming.
- Expertise in Data Preprocessing like Data Gathering, Data Analyzing, Data Munging, Data Transformation, Data Visualization.
- Skilled in using python libraries like Pandas, Numpy, Scikit-learn, Matplotlib, tensor-flow, Keras.
- Expertise in with Anaconda Environment and on-premise Microsoft Machine Learning Servers.
- Worked as ML Environment support administrator with R and Python with H2O Framework.
- Experience in deploying and publishing ML models using IIS and Windows Task Scheduler.
- Operationalized ML models by building stable environment and dependencies using python Flask.
- Comprehensive knowledge of statistical concepts like correlation, regression, chi-square, normality test, t-test and hypothesis testing.
- Expertise in Text Analysis using NLP with Spacy and Data Analysis (EDA) by working with other functional teams, Business Analysts and Data Architects.
- Worked on ML projects such as Credit Card Defaulter Prediction, Sentiment Analysis using Text Mining, Customer Behavioral Scoring, Income estimation, CPI value prediction etc.
- Worked on Data Lake Build (Using ETL, Hadoop, Hive), Claim Book of Records Project and Health Care Project.
- Recognized with Certificate of Excellence in recognition of contribution towards Delivery Excellence.
- Achieved award in recognition of contribution towards commitment on client deliverables
- Effective communicator with excellent analytical, organizational and interpersonal skill
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Portfolio Projects
Description
Description: Detected how the consumer is reacting to newly launch banking product, Performed sentiment analysis using overall conversation about them as well as product-related discussions. Deeper analysis of product-related discussions gives banks detailed insights. We developed model using Spacy
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Description
Description: As part of HSBC Retail Credit Risk analytics for MENA region, We applied Machine learning techniques to estimate customer income. We developed a ML model using regression models R with H2O framework on a Microsoft Machine Learning Platform. The banking operations are using this model to target right customers for right products.
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Description: As part of HSBC Retail Credit Risk analytics, We applied Machine learning techniques to get customer credit scoring . We developed a ML model using GBM algorithm in R with H2O framework on Microsoft Machine Learning Server Platform. The banking operations are using this model for credibility of customers while sectioning the loans.
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Description
Description: As part of ST risk analytics initiative project, We applied Machine learning techniques to address financial risk related problems. We developed a ML model using logistic regression to predict defaulter. The banking operations are using this model for prediction of defaulters on monthly basis and hence necessary alerts are being taken care in advance
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40036.8 USD / Year (Expecting)
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Start Date / Notice Period end date: 2022-04-30