Data Analyst Resume

SUMMARY:

Around 3 years of experience as Data analyst with excellent communication skills.
Very passionate about application data analysis, Machine learning techniques on real time data to solve complex business problems

TECHNICAL SKILLS:

Languages: Python (NumPy, Pandas, Scikit - learn, Matplotlib, Seaborn, NLTK), Scala, R, SQL

Machine learning: Linear Regression, Logistic Regression, SVM, Naive Bayes, kNN, K-Means, Decision trees, Random Forest, Dimensionality Reduction, Gradient Boosting

Statistical packages: SPSS

Big Data framework: Apache Spark, data bricks.

Database: Microsoft SQL server, MS Access.

IDE: Jupyter notebook, Databricks notebook and sublime

Code repository: GitHub.

Cloud: AWS

Data visualization/Diagramming tools: Tableau, MS Visio

Deep learning: TensorFlow, Keras

PROFESSIONAL EXPERIENCE:

Confidential

Data Analyst

Responsibilities:

Experienced in using Python to collect, cleanse the raw data from various sources and making them ready to analyze.
Use techniques like Matplotlib, Seaborn in Python and tools like Tableau to visualize the data in different forms.
Looking into the customer data to observe the purchasing behavior and segregated them into different customer segments using Classification techniques
Built predictive models using regression techniques and boosting techniques such as XGBoost to improve the models
Experience in using in IDEs such as Jupyter notebook, Databricks notebook and Sublime text to build models.
Use of customer data from the database and evaluate customer credit rating and sales targets and achievements

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