Data Science Research Assistant Resume

SUMMARY:

Skilled in statistics, SQL, Python and R programming.
Knowledge and understanding of Machine Learning, Cloud Computing and Big Data frameworks and visualization tools.
Hands - on experience in DevOps methodology and related tools like Git, Docker.
Excellent communication, time management, and problem-solving skills. Open to relocation.

TECHNICAL SKILLS:

Database Modeling

Data Models

MySQL

SQL

Clustering

Data Analytics

Data Mining

Data Science

Hadoop

Machine Learning

Mongodb

Natural Language Processing

NLP

Power Bi

Sentiment Analysis

Algorithm

Git

Javascript Frameworks and Libraries

React

Python

Keras

Matplotlib

Numpy

Pandas

R Language

R Programming

Apriori Algorithm

Association Rules

Deep Learning

K-Means

Logistic Regression

Principal Component Analysis

Support Vector Machine

SVM

Data Quality

DEV OPS

Devops

Docker

Minitab

WEB Based

WEB-Based

Tableau Software

Tableau

Systems Engineering

Quantitative

Quantitative Analysis

Trading

Risk Management

Research Analysis

Closing

Business Intelligence

Product Sales

Microsoft Excel

Microsoft Powerpoint

PowerPoint

MICROSOFT WORD

Word

Test Reports

Documentation

Time Management

Medical Device

Biomedical

SNP

Statistics

Visualization

Problem-Solving

EXPERIENCE:

Confidential

Data Science Research Assistant

Responsibilities:

Develop guidance mechanisms that helps analysts develop trust in the outcome of the automated methods, such as black-box machine predictive models.
Topology Identification using Time Series Analysis
Identify layout of Systems Engineering Building (SEB) at Confidential to determine temperature correlations using SEB dataset.
Conduct dynamic time warping and K-means clustering methods to find correlations and create data visualizations.
Content Moderation using NLP Approaches to identify misinformation
Perform research analysis by leveraging 10M+ tweets to develop sentiment analysis and subjectivity analysis models that help identify misinformed tweets.
Coded Python programs to calculate TF-IDF vectorization to further perform topic modeling.

Confidential

Development Engineer (Consultant)

Responsibilities:

Ensured proper application of Design Controls and risk management activities to maintain high standards of data quality and integrity for medical device products.
Improved verification testing and assessed verification reports as per statistical guidance for design verification to cover any missing gaps in existing documentation.
Conducted quantitative analysis using Minitab to justify sample size for the existing verification test reports and validated processes using design of experiments (DOE).
Investigated and analyzed patient complaints data and generated reference reports
Interpreted MAUDE database and query the data using SQL to establish occurrences.
Worked extensively on data visualizations in Power BI and Excel to analyze product sales.
Effectively led Design Reviews and performed review and approval on closing the DHF.

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