SONALI SHINTRE

adms0b@r.postjobfree.com https://github.com/sonalishintre www.linkedin.com/in/sonalishintre +1-518-***-**** New York, NY

Looking for Data Science/Software position with solid background in Machine Learning and Python, R programming skills.

EDUCATION:

The City College of New York, New York Aug/2018 - June/2020 Master’ s in Data Science and Engineering

Oxford College of Engineering, Bangalore, India June/2013 - Sept/2017 Bachelor of Engineering in Information Science and Technology

TECHNICAL SKILLS:

• Programming Language: Python, SQL, R

• Data Visualization: Tableau, Power BI

• Packages: Scikit-Learn, Pandas, NumPy, Matplotlib, Seaborn, NLTK, Keras, TensorFlow, MNE-python

• Machine Learning: Statistical analysis, supervised/unsupervised algorithms, hypothesis testing, classification, regression, clustering, decision tree, SVM, random forest, NLP, deep learning, CNN

EXPERIENCE:

Data Analyst, Institute for Ultrafast Spectroscopy and Lasers, CCNY Oct/2020 – Present

• Utilized Microsoft Excel to categorize budget reports into detailed pivot table to develop financial strategy

• Participated in collecting, organizing and interpreting data along with researcher. Assisted students in laser labs

• Established efficient workflow processes, oversaw office inventory activities, including ordering and requisitions

• Developed complex reports, assist in writing the technical reports, papers, proposals.

Data Analyst Intern, Supplycopia July/2020 – Oct/2020

• Implemented data pre-processing using R for data cleansing containing over million entries and generating valuable insights from the clean dataset. Translating numbers and facts to inform strategic business decisions

• Developed test cases and SQL test scripts based on detail data analysis, functional design and ETL specifications

• Optimized data collection procedures and generated reports. Web Scraping from a given healthcare websites

• Used Python, R, SQL, Excel, Scrapy and other python libraries

CodeLabs Intern, CodeDay July/2020 - Aug/2020

• Developed stack ML model to classify microscopic wood images, deep learning techniques like Convolutional Neural Networks (CNN) for texture classification. Model performed well with the accuracy of 94.6% on the test data

• Selected as one of the top 5 data science projects. Worked in team of 3 with Mr. Keith Callenberg as mentor

Administrative Assistant, Institute for Ultrafast Spectroscopy and Lasers, CCNY Sept/2018 - May/2020

• Content editor for IUSL website, published Newsletters, Annual reports, prepared and organized records

• Prepared financial and administrative reports, placed orders, organized departmental mail, answered phone calls

PROJECTS:

Steel Defect Detection: (Used Python, pandas, Scikit-Learn, Classification/regression algorithm, TensorFlow)

• ML model to predict location and type of defects in steel sheets produced during manufacture. Performed Binary classification, multiclass classification to finds cracks, type of defects. UNET model to find location of defect on sheet EEG Data Analysis, Visualization

and Image Classification: (Used Python, MNE-Python, TensorFlow)

• Understanding the behavior and cognitive ability of the human brain, using BrainVision Analyzer. visualize spatial distribution of brain activity. Published the paper (under review).

Zebra Crossing Detection and Localization: (Used MATLAB)

• Identify crosswalk for visually impaired people. Preprocessing, equalization, thresholding, find contours, Hough Transform. Constructed angle profile to infer orientation with respect to crosswalk

CERTIFICATIONS:

• Udacity Nano Degrees: Machine Learning, SQL (In process)

• Coursera: IBM Data Science Professional, Google Data Analytics, AWS with Machine Learning

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