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Data Analyst, Python

Location:
Bangalore, Karnataka, India
Salary:
800000
Posted:
October 28, 2019

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Resume:

Harshith Shettigar

LinkedIn Profile

+91-974*******

**************@*****.***

Data Analyst with a good understanding of Math, Machine Learning and Probability and Statistics. An astute learner aspiring to be subject matter expert.

Education

[MCA (Masters of Computer Applications)] / [Sahyadri College] (2013-2016)

Graduated with 75.67%.

Skills

Analytical Tools

Analytical Techniques

Python packages

Experience

[Data Analyst] / [Tech Mahindra] [Oct 2018] – [Present]

Proficient in gathering requirements, extracting, manipulating and analyzing massive datasets and converting data into actionable information.

Executed Complex SQL Queries in PostgreSQL.

Sound knowledge in Python, Machine Learning, Predictive Modelling, Statistical methods.

Performed Data Wrangling in python using pandas and also to deal with the missing values.

Knowledge of PIVOT tables, PIVOT Charts.

Generated customer interactive dashboards using Tableau as well as Excel.

[SAP MH Configuration] / [Tech Mahindra] [Jan 2017] – [Oct 2018]

Interactively worked with AOA, EUR & AMS zone users.

Experience in Go-Live, End user training and post production support.

Sending daily reports and conducting DOR for focused KPI achievement.

Certifications

IBM Data Science professional Certificate (9 Course Specialization - Coursera)

Python for Everybody (5 Course Specialization by University of Michigan on Coursera)

Microsoft Certified: Programming in HTML5 with JavaScript and CSS3

Microsoft Excel - Excel from Beginner to Advanced (Udemy)

POCs Done (Kaggle Projects)

Titanic Survivability Project (Logistic Regression, Python)

To build a predictive model that answers the question: “what sorts of people were more likely to survive?”

Predict Customer clicks on FB ads (Logistic Regression, Python)

To analyze customer behavior by predicting which customer clicks on the advertisement.

Cancer Classification (Support Vector Machines, Python)

Predicting if the cancer diagnosis is Benign (Cancer is present, but will not spread throughout the body)

or Malignant (Cancer is present, and it will spread throughout the body and needs doctor intervention) based on several features.

Excel, SQL, Tableau

Python for Data Science

SVM, KNN, Trees

Linear, Logistic Regression

Matplotlib, Seaborn

NumPy, SciPy, Pandas

Cluster Analysis, Segmentation

Sklearn, Statsmodels



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