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Definition of Reputation Credits
Manisha Madane ( Data Scientist )
Email Id: [email protected] Mobile No: 7378918443
1. 4.5+ years of experience in IT and comprehensive industry knowledge of Machine Learning, Data Analysis, Predictive Analysis, Data Manipulation, Data Mining, Data Visualization and Business Intelligence.
2.Experience in performing Feature Selection, Linear Regression, Logistic Regression, k - Means Clustering, Classification, Decision Tree, Supporting Vector Machines (SVM) , Naive Bayes, K-Nearest Neighbours (KNN) , Random Forest, and Gradient Descent,
algorithms to train and test huge data sets.
3.Adept in statistical programming languages like Python. Expertized in Python data extraction and data manipulation, and widely used python
libraries like NumPy, Pandas,Spacy and Matplotlib for data analysis.
4.Extensively worked on other machine learning libraries such as Seaborn, SciKit learning,SciPy for machine learning and familiar working with NLTK.
5.Experience in Text Analytics, developing different Statistical Machine Learning, Data Mining solutions to various business problems and generating data visualizations using R,Python.
6.Hands on experience in implementing LDA, Naive Bayes and skilled in Random Forests, Decision Trees, Linear and Logistic Regression, SVM, Clustering, Principle Component Analysis.
8.Quick learner having strong business domain knowledge and can communicate the business data insights easily with technical and nontechnical clients.
Work Experience
Data Scientist/NLP Engineer • Entercoms
May 2019 - Present
Responsibilities :
1. Responsible for developing system models, prediction algorithms, solutions to prescriptive analytics problems, data mining techniques, and/or econometric models.
2. Communicate the results with the operations team for making the best decisions and collect data needs and requirements by interacting with the other departments.
3. Demonstrated and built statistical/machine learning systems to solve large-scale customer-focused problems and leveraging statistical methods and applying them to real - world business problems
4. Perform Data Profiling to learn about behaviour with various features of turnover before the hiring decision, when one has no on-the-job behavioural data.
5. Performed preliminary data analysis using descriptive statistics and handled anomalies such as removing duplicates and imputing missing values.
6. Application of various machine learning algorithms and statistical modelling, like decision trees, text analytics, natural language processing, NLP,supervised and unsupervised, regression models, social network analysis, neural networks, deep learning, SVM, clustering to identify volume using Scikit-learn package in python
7.Performed data cleaning and feature selection using PCA, TF-IDF Vectorization.
8.Understanding business problems and analysing the data by using appropriate statistical models to generate insights.
9.Developed NLP models for Topic Extraction, Sentiment Analysis Identify and assess available machine learning and statistical analysis libraries including regressors, classifiers, statistical tests, and clustering algorithms .
10.Work with the NLTK library for NLP data processing and find the patterns. Categorize comments into different things using text Analytics.
Environment : Python 2.x, R, SQL Server 2012, Microsoft Excel,
Junior Data Science Consultant • Altius
April 2018 - April 2019
Responsibilities :
1.Analysing large data sets by applying machine learning techniques and developing predictive models, statistical models and developing and enhancing statistical models by leveraging best-in-class modelling techniques.
2,Well experienced in Normalization and De-Normalization techniques for optimum performance in relational and dimensional database environments.
3.Understanding requirements, the significance of weld point data, energy efficiency using
large datasets
4.The model was developed to identify risk undertaken by each customer using machine algorithms. This analysis helps companies to tighten the lending process by identifying risky and default investments. Also, the analysis involves the various criteria in order to point out the most probable bench.
mark in the sector of customer rating, product analysis, quality etc.
Environment : Python 2.x/3.x, Scikit-Learn/SciPy/NumPy/Pandas/Matplotlib/Seaborn,
Machine Learning algorithms, Random Forest, Gradient Boosting tree, Feature Engineering,
Feature Section .
.
Data Analyst • Sipra Infotech
January 2016 - March 2018
Responsibilities :
1.Collaborated with data engineers and an operation team to implement the ETL process, wrote and optimize SQL queries to perform data extraction to meet the analytical requirements.
2.Wrangled data, worked on large datasets, acquired data and cleaned the data, analysed trends by making visualizations using python
3.Used Python to develop a variety of models and algorithms for analytic purposes.
4.Conducted analysis and patterns on customers' shopping habits in of a different locations, different categories and different months by using time series Modelling techniques.
5.Used RMSE/MSE to evaluate different models' performance.
6.Designed rich data visualizations to model data into human-readable form with Matplotlib.
Environment : Python, SQL, Matplotlib
Education
2014 - 2016
Pune University
M.E IT
2011 - 2014
Solapur University
Computer Science
Apr 2018 - Jan 2020
Solapur University
DIPLOMA Computer Technology
2008 - 2011
Maharashtra State Board
Computer Science
Skills
Languages
- Positive Attitude
- Comprehensive
- Working hard
- Honest
- Classification
- Communication
- Disciplined
- Prediction
- Analysing
- Motivated
- Chinese - Native
- English - Professional
Manisha Madane ( Data Scientist )
Email Id: [email protected] Mobile No: 7378918443
1. 4.5+ years of experience in IT and comprehensive industry knowledge of Machine Learning, Data Analysis, Predictive Analysis, Data Manipulation, Data Mining, Data Visualization and Business Intelligence.
2.Experience in performing Feature Selection, Linear Regression, Logistic Regression, k - Means Clustering, Classification, Decision Tree, Supporting Vector Machines (SVM) , Naive Bayes, K-Nearest Neighbours (KNN) , Random Forest, and Gradient Descent,
algorithms to train and test huge data sets.
3.Adept in statistical programming languages like Python. Expertized in Python data extraction and data manipulation, and widely used python
libraries like NumPy, Pandas,Spacy and Matplotlib for data analysis.
4.Extensively worked on other machine learning libraries such as Seaborn, SciKit learning,SciPy for machine learning and familiar working with NLTK.
5.Experience in Text Analytics, developing different Statistical Machine Learning, Data Mining solutions to various business problems and generating data visualizations using R,Python.
6.Hands on experience in implementing LDA, Naive Bayes and skilled in Random Forests, Decision Trees, Linear and Logistic Regression, SVM, Clustering, Principle Component Analysis.
8.Quick learner having strong business domain knowledge and can communicate the business data insights easily with technical and nontechnical clients.
Work Experience
Data Scientist/NLP Engineer • Entercoms
May 2019 - Present
Responsibilities :
1. Responsible for developing system models, prediction algorithms, solutions to prescriptive analytics problems, data mining techniques, and/or econometric models.
2. Communicate the results with the operations team for making the best decisions and collect data needs and requirements by interacting with the other departments.
3. Demonstrated and built statistical/machine learning systems to solve large-scale customer-focused problems and leveraging statistical methods and applying them to real - world business problems
4. Perform Data Profiling to learn about behaviour with various features of turnover before the hiring decision, when one has no on-the-job behavioural data.
5. Performed preliminary data analysis using descriptive statistics and handled anomalies such as removing duplicates and imputing missing values.
6. Application of various machine learning algorithms and statistical modelling, like decision trees, text analytics, natural language processing, NLP,supervised and unsupervised, regression models, social network analysis, neural networks, deep learning, SVM, clustering to identify volume using Scikit-learn package in python
7.Performed data cleaning and feature selection using PCA, TF-IDF Vectorization.
8.Understanding business problems and analysing the data by using appropriate statistical models to generate insights.
9.Developed NLP models for Topic Extraction, Sentiment Analysis Identify and assess available machine learning and statistical analysis libraries including regressors, classifiers, statistical tests, and clustering algorithms .
10.Work with the NLTK library for NLP data processing and find the patterns. Categorize comments into different things using text Analytics.
Environment : Python 2.x, R, SQL Server 2012, Microsoft Excel,
Junior Data Science Consultant • Altius
April 2018 - April 2019
Responsibilities :
1.Analysing large data sets by applying machine learning techniques and developing predictive models, statistical models and developing and enhancing statistical models by leveraging best-in-class modelling techniques.
2,Well experienced in Normalization and De-Normalization techniques for optimum performance in relational and dimensional database environments.
3.Understanding requirements, the significance of weld point data, energy efficiency using
large datasets
4.The model was developed to identify risk undertaken by each customer using machine algorithms. This analysis helps companies to tighten the lending process by identifying risky and default investments. Also, the analysis involves the various criteria in order to point out the most probable bench.
mark in the sector of customer rating, product analysis, quality etc.
Environment : Python 2.x/3.x, Scikit-Learn/SciPy/NumPy/Pandas/Matplotlib/Seaborn,
Machine Learning algorithms, Random Forest, Gradient Boosting tree, Feature Engineering,
Feature Section .
.
Data Analyst • Sipra Infotech
January 2016 - March 2018
Responsibilities :
1.Collaborated with data engineers and an operation team to implement the ETL process, wrote and optimize SQL queries to perform data extraction to meet the analytical requirements.
2.Wrangled data, worked on large datasets, acquired data and cleaned the data, analysed trends by making visualizations using python
3.Used Python to develop a variety of models and algorithms for analytic purposes.
4.Conducted analysis and patterns on customers' shopping habits in of a different locations, different categories and different months by using time series Modelling techniques.
5.Used RMSE/MSE to evaluate different models' performance.
6.Designed rich data visualizations to model data into human-readable form with Matplotlib.
Environment : Python, SQL, Matplotlib
Education
2014 - 2016
Pune University
M.E IT
2011 - 2014
Solapur University
Computer Science
Apr 2018 - Jan 2020
Solapur University
DIPLOMA Computer Technology
2008 - 2011
Maharashtra State Board
Computer Science
Skills
Languages
- Positive Attitude
- Comprehensive
- Working hard
- Honest
- Classification
- Communication
- Disciplined
- Prediction
- Analysing
- Motivated
- Chinese - Native
- English - Professional