Sahithi S +91-910*******

Data Analyst / Jr Data scientist adg1zz@r.postjobfree.com

https://github.com/savvy-sahi

https://www.linkedin.com/in/sahithi-4393711a1/

PROFESSIONAL SUMMARY

• Having 2 years of experience in data analysis and predictive modelling with technical know-how in various data science and analysis tools.

• Hands on experience in supporting data analysis projects pertaining to healthcare/pharma and financial industry (Banking/Insurance) industries.

• Experience in ETL implementation and ad hoc query for various databases such as MS SQL server, Oracle, PostgreSQL and MySQL.

• Expertise in python and its extensively used packages such as pandas, NumPy, matplotlib, scikit- learn, keras, TensorFlow, nltk, Spacy.

• Well-versed in statistical analysis, supervised machine learning to deliver relevant business insights and optimize key processes.

• Proficient in data visualization tools such as Tableau and python visualization packages such as Matplotlib, Seaborn, Plotly, ggplot to create interactive dashboards and actionable reports.

• Experience in implementing machine learning and deep learning techniques such as neural networks, image classification and possess conceptual knowledge on Natural Language Processing (NLP). SKILLSET SUMMARY

Software Microsoft Office Suite, Jupyter notes, PyCharm, Anaconda, google Collab, Command line, Tableau, Rstudio, TensorFlow, Keras, Scikit-learn, Advanced Excel, VBA

Databases Oracle 10g, 11g; SQL Server, PostgreSQL

Languages Python, PL/SQL, SQL, R

Python Packages (EDA) Pandas, NumPy, SciPy, Matplotlib, Plotly, Seaborn, datetime, ggplot Visualization Tableau, Plotly, Matplotlib, Seaborn Version Control Git

Skills Feature Engineering, Exploratory data analysis, Data visualization, Regular Expressions, Data wrangling, Statistical analysis, Machine Learning, Deep Learning, Sentiment Analysis, NLP.

2

EXPERIENCE

Idol Soft Inc., Hyderabad [ AUG 2019 – TILL DATE ] DATA ANALYST / JR DATA SCIENTIST

Project Title: Chronic Disease Risk Stratification and Predictive Modelling using Machine learning Extensively supporting the client IQVIA and the objective of the project is to analyze patient population to improve care provided to them in chronic conditions to reduce inefficiency and waste while patient’s risk is reduced thereby enhancing health-related quality of life and cost containment.

• Extracted pertinent insights from multiple data sources like EDW, cost reports, Electronic Health Record

(EHR), EMR’s, billing data and patient satisfaction data with the help of data analysis tools and RDBMS.

• Performed data analysis on patient health data to separate patient populations into stratified classes for efficient risk stratification to proactively better manage the high risk, high cost patients.

• Analysed chronic disease data such as diabetes registries to discover trends on movement of patients within risk categories. Built models to predict if HbA1c Measurement had an impact on hospital readmission rates using clinical patient records.

• Created intuitive reports and dashboards to communicate patterns, trends and outcomes to aid the organisation in managing its patient population through evidence-based medicine. Technical Stack: SQL, PostgreSQL, Tableau, Python, Scikit-learn, Tensorflow, Keras. Project Title: To build an effective credit scoring model to tailor insurance pricing strategies. Extensively supported for CreditEnable and the objective of the project was to build an effective credit scoring model to tailor pricing strategies based on the likelihood of defaults.

• Developed and implemented an effective credit scoring model that supports Banking / Insurance operations.

• Performed data cleaning such as imputing missing values, outlier analysis to ensure data quality, consistency, integrity using software such as Pandas, NumPy and SQL.

• Performed feature engineering such as analyzing feature importance, feature normalization, label encoding using Scikit-learn to increase model accuracy and efficiency.

• Built various credit scoring machine learning models and made use of various evaluation and performance measures to assess the financial health of SMEs. Evaluated the model using performance measure Gini and area under ROC. ROC demonstrated 30% better accuracy than the competing company. Technical Stack: SQL, PostgreSQL, Advanced Excel, Python, Scikit-learn. Idol Soft Inc., Hyderabad – Jr DATA ANALYST (Intern) [ FEB 2019 – JULY 2019 ]

• Designed relational database management system using UML – Activity Diagram, Use Case and Entity- Relationship Diagram (ERD).

• Performed various ad hoc data related tasks.

EDUCATION

BACHELOR’S IN COMPUTER APPLICATIONS, HYDERABAD

Osmania University

[2016 – 2019]

8.77

CGPA

BACHELOR’S IN INFORMATION SYSTEMS AND MANAGEMENT,

SINGAPORE

Singapore Institute of Management (University of London) (Disconn)

[2015 – 2016]

A

ADVANCED DIPLOMA IN INFORMATION TECHNOLOGY, SINGAPORE Management Development Institute of Singapore

[2014 – 2015]

A

3

GITHUB PROJECTS

• Twitter Sentiment Analysis using R:

Performed sentiment analysis using R on sentiments towards various social media trends using multiple lexicons, Twitter API and visualization tools like ggplot2 and word clouds. Technical Stack: RStudio, ggplot2, Tidytext, wordcloud, lexicon, syuzhet, sentimentr

• Predicting Car Sales:

Performed EDA and created a univariate and multivariate model using KNN to predict car sales.

• Loan-Prediction:

Performed predictive modelling on discrete values to determine whether a loan must be approved or disapproved using various classification algorithms. Technical Stack: Jupyter notes, matplotlib, Sklearn, Pandas, NumPy, linear models (svm, Logistic Regression, randomforests, XGboost).

• Application Analysis:

Performed exploratory data analysis on the apps available on App store and Play Store to determine the app category which is more likely to yield greater profitability considering category competition dynamics.

• Lottery Addiction Combinatorics:

Developed conditional probability combinatorics that are to be used in an application aimed at both preventing and treating lottery addiction by helping people better estimate their chances of winning. CERTIFICATIONS

Dataquest.io:

Advanced SQL for Data Analysis

Data Analyst and Data Scientist paths

Data Analysis in Business course

APIs and Web Scraping

Udemy:

Tableau 2020 A-Z: Hands-on Tableau Training for Data Science Cognitive class:

Python for Data Science

Google:

Machine Learning crash course

Coursera:

Introduction to Statistics and Data Analysis in Public Health

Artificial Intelligence for Medicine Specialization

Excel/VBA for Creative Problem Solving

EXTRA CURRICULAR ACTIVITIES

Participated in 17th Senior Women amateur National Boxing Championship.

Winning Captain for bhavans summer cricket tournament Hyderabad.

Contact this candidate