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Mental Health Data Analyst

Location:
Mountain View, CA
Posted:
November 20, 2020

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Resume:

Khushboo Patel

Website: https://kpatel**.wixsite.com/website-1 Phone: 628-***-**** Email: adh0if@r.postjobfree.com

LinkedIn: www.linkedin.com/in/khushboo-patel1 Location: San Francisco, CA GitHub: https://github.com/khushboop117

SUMMARY

Enthusiastic data scientist eager to contribute to team success through hard work, attention to detail and excellent organizational skills. Clear understanding of Python and R. Motivated to learn, grow and excel in Data related industry. Excellent reputation for resolving problems, improving customer satisfaction, and driving overall operational improvements.

EDUCATION

Master of Science – Data Science, University of the Pacific, San Francisco (GPA: 3.58) Aug 2019 - May 2021

Bachelor of Technology in Instrumentation & Control Engineering, Nirma University, India (GPA: 7.93/10) Aug 2015 – May 2019

Relevant Courses: Machine Learning(hypothesis testing, regression), Neural Networks, Analytics Computing, RDBMS, Data Wrangling(Natural Language Processing), Time Series Analysis, Data Engineering, Frequentist Statistics, Bayesian Statistics, Linear Algebra, NoSQL, Data Visualization, Analytics storytelling, Customer Analytics

TECHNICAL SKILLS

Tools: Jupyter Notebook, Microsoft Ofiice, Tableau, AWS, Google Colab, PyCharm, Spyder, Git, SAS, Stata, AWS Redshift

Scripting Languages/ Web Designing/Database: R/R-Studio, Python, SQL, C/C++, HTML, CSS, SQL, MongoDB, Cassandra, Redis, Memcached, neo4j, data pipelines, Microsoft Powerpoint, Microsoft Excel

Frameworks: Hadoop, MapReduce, Hive, SciKit-Learn, NumPy, Plot.ly, Pandas, NLTK, Random Forest, Xgboost, TensorFlow, Keras, Matplotlib, StatsModel, Scipy, Seaborn, streamlit, ggplot

PROFESSIONAL EXPERIENCE

Machine Learning Intern - Sunflowee Biztech Pvt Ltd 05/2020 - 08/2020

Proposed solution for real time analysis from CCTV feed for person counter using OpenCV in Google Colab using GPU runtime by making the process faster by 30%.

Implemented deep learning model line YOLO model for person and object detection and Caffemodel for gender detection and age group prediction using CNN architecture. Additionally, added the options to upload the file from the device or directly from YouTube link.

Built interactive dashboard with a lot of visualization to showcase the analytical aspects using streamlit with features to download the processed video and analytical csv file for the user.

Data Analyst - Moodcafe Wellness Solutions 12/2017 - 12/2018

●Designed surveys to know the mental health awareness in India and compile market analysis reports for various verticals in mental healthcare. Created clean, formatted datasets with accompanying data dictionaries for both internal and external use. Derived the organizational chart for various mental health care provider and payer networks. Identified target group, present problems, awareness and accessibility of mental health in India by analyzing data collected via primary market research.

●Worked with the research team to participate in study design of their individual projects and determined appropriate statistical models for analysis. Assessed detailed analysis, generated insights and visualization and published reports. Closely worked with CEO and management and successfully interpreted data in order to draw conclusions for managerial action and strategy.

●Won 1st prize and INR 60000 in Startathon - a business-plan competition at IIM Ahmedabad.

Instrumentation Intern - Siemens 06/2018 - 07/2018

●Contributed to the enhancement of logic design on communication protocol model for DCS system and field devices along with a comparison sheet of different protocols.

●Proposed a solution to reduce the cost of the turbine lube oil system by 40% and designed a logic in PLC.

Research Intern - Oil and Natural Gas Corporation

PROJECTS

Crime and Fraud Mapping (Geographic Visualization) (Python) 2019

Analyzed and interpreted raw datasets, conducted reports, performed accurate, successful data analysis.

Performed exploratory data analysis and visualization for data set from Kaggle in Python (Jupyter Notebook) with 223958 x 34 columns along with data cleaning and adaptation by removing all the unnecessary and irrelevant data and by adding an aggregation column.

Detected reasons for crime by step by Step Hierarchical Clustering analysis using Agglomeration method and dendrogram.

Coupon Recommendation Tool (Python) 2019

Collected, cleaned and provided modeling and analyses of structured and unstructured data used for major business initiative.

Created a recommendation engine for email coupon campaigns in Python for the university students where student will be given coupons based on their characteristics and food habits in Python.

Predicted the food liking of a person using data mining tool by clustering data with k-means, KNN clustering and using library sklearn.cluster.

Used predictive analysis such as machine learning and data mining techniques to forecast the food coupon liked by the student.

Lift management system (C++) 2016

Designed and simulated an integrated lift management system using C++ language to efficiently run five parallel lifts of a building.

Develop an algorithm which reduces the waiting and travelling time in elevators.

PUBLICATION May 2019

Title: Comparative analysis of different methods for fruit quality determination (IEEE - CCECE 2019)



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