Zamir S.

Zamir S.

Data Scientist- Technical Specialist 3 (Machine Learning Architect)

Greater Noida , India

Experience: 14 Years

Zamir

Greater Noida , India

Data Scientist- Technical Specialist 3 (Machine Learning Architect)

36000 USD / Year

  • Immediate: Available

14 Years

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About Me

Machine Learning Expert (individual Contributor)Leading Team of 5 Data Scientists...

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Portfolio Projects

Description

Individual Contributor

Developed a cold start accessories recommendation model for telecom organization Technologies/Tools: Python, Knn, pandas, numpy and matplotlib Domain: Telecom / Sales

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Description

Individual Contibutor

Developed a personalized accessories recommendation model for telecom organization Technologies/Tools: Python, Kmeans, pandas, numpy and matplotlib Organization: HCL Technologies Domain: Telecom / Sales

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Description

Individual Contributor

Working on text classification (natural language processing) by using transfer learning of google pre trained word2vec (GoogleNews-vectors-negative300) model. Technologies/Tools: Keras, CNN, LSTM, Python, pandas, numpy, word embedding, nlp. Domain: Telecom / Sales

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Description

Developed a regression model by using random forest regression of h2o to predict number of bugs in software in production. Able to achieved around 0.83 r squared.

Technologies/Tools: h20, distributed random forest regression, steam, R.

Domain: Software

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Description

Developed aclassification model topredict the customers who can upgrade mobile.

Able to achieved 79?curacy.We have used GBM of h2o.

Technologies/Tools: h20, GBM, steam, python, pandas, numpy, SMOTE.

Domain: Telecom /Sales

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Description

Developed a classification model to predict the recurrence of hepatitis C disease after the completion of treatment. Able to achieved the accuracy of 91%.We have used ensemble learning by using random forest, GBM and SVM.

Technologies/Tools: R, SMOTE, ensemble learning, random forest, gbm, svm, baruta, pca, caret

Domain: Pharmaceuticals

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Description

Developed a classification model to reduce the false positiveinstances MBIalgorithm. Able to reduce the false positive cases by 7%.We have fine-tuned the already used random forest and by using various techniques of variable selection.

Technologies/Tools: R, baruta, leaps, pca, SMOTE, under sampling, logistic regression, random forest, svm, gbm

Domain: Pharmaceuticals

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Description

Developed an association rule mining model to find patterns in the variables - which accident conditions frequently occur together. We have used apriori algorithm of R.

Technologies/Tools: R, apriori

Domain: Insurance

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Description

Developed a sentiment analysis model for comments written by employee in yearly engagement survey. This is polarity based model to classify the comments in Highly Positive, Positive, Neutral, Negative and Highly Negative.

Technologies/Tools: Python, VADER

Domain: HR

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Description

Developed a regression model to predict the emission of various cars as per Environmental Protection Agency (EPA). Able to achieved the accuracy of 78%.We have used ridge regression of R.

Technologies/Tools: R, ridge regression

Domain: Automobiles

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Description

Developed classification model to predict whether person can be prospective Bank Customer. Able to achieved the accuracy of 79%.We have random forest of R and also used clustering to get better prediction.

Technologies/Tools: R, SMOTE, K-means, random forest

Domain: Banking

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Description

Technologies/Tools: Python, Knn, pandas, numpy and matplotlibOrganization: HCL TechnologiesDomain: Telecom / Sales

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Description

Technologies/Tools: Python, Kmeans, pandas, numpy and matplotlibOrganization: HCL TechnologiesDomain: Telecom / Sales

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Description

Technologies/Tools: Keras, CNN, LSTM, Python, pandas, numpy, word embedding, nlp.Organization: HCL TechnologiesDomain: Telecom / Sales

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Description

Technologies/Tools: h20, distributed random forest regression, steam, R.Organization: HCL TechnologiesDomain: Software

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Description

Technologies/Tools: h20, GBM, steam, python, pandas, numpy, SMOTE.Organization: HCL TechnologiesDomain: Telecom /Sales

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Description

Technologies/Tools: R, SMOTE, ensemble learning, random forest, gbm, svm, baruta, pca, caretOrganization: Tata Consultancy ServicesDomain: Pharmaceuticals

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Description

Technologies/Tools: R, baruta, leaps, pca, SMOTE, under sampling, logistic regression, random forest, svm, gbmOrganization: Tata Consultancy ServicesDomain: Pharmaceuticals

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Description

Technologies/Tools: R, aprioriOrganization: Aon HewittDomain: Insurance

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Technologies/Tools: Python, VADEROrganization: Aon HewittDomain: HR

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Description

Technologies/Tools: R, ridge regressionOrganization: Aon HewittDomain: Automobiles

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Description

Technologies/Tools: R, SMOTE, K-means, random forestOrganization: Aon HewittDomain: Banking

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Description

Technologies/Tools: R, Random forest

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Description

Technologies/Tools: Core Java, ExtjsOrganization: Aon HewittDomain: Absence Management

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Description

Technologies/Tools: Core java, JspOrganization: Aon HewittDomain: HM, DB, DC

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