

Data Scientist familiar with gathering, cleaning and organizing data for use by technical and non-technical personnel. Advanced understanding of statistical, algebraic and other analytical techniques. Highly organized, motivated and diligent with significant background in Astrophysics, Computational Epidemiology, Python, SQL, Machine Learning, and NLP.
Machine learning expertise
Data analysis expertise
Natural Language Processing
Data Analysis
Data mining
Statistical Modeling
Data Visualization
Power BI
Tableau
Mathematical Modeling
Predictive Modeling
Office Suites (Excel, Word,PowerPoint, Outlook)
Communication
Python programming
R programming
Agile methodology
Problem-solving
Team building
Excellent communication
Time management
Linux and bash scripting
Virtual Machines
Containerization (Docker)
High-performance computing (HPC)
Version control proficiency (eg Git)
Research Methodology
Epidemiological modeling
Cosmological simulations
Astrophysics data analysis
Bayesian inference methods
STAN
ICH Good Clinical Practice
Train the Trainer
Deep Learning: Getting Started
Data Science on Google Cloud Platform: Building Data Pipelines
NLP with Python for Machine Learning Essential Training
Applied Machine Learning: Ensemble Learning
Artificial Intelligence Foundations: Machine Learning
Programming Foundations: Artificial Intelligence
Amazon Web Services (AWS) Machine Learning Essential Training
ICH Good Clinical Practice
Machine Learning with Python: Decision Trees
Machine Learning with Python: Foundations
Machine Learning with Python: k-Means Clustering
Hands-On Data Science using SQL, Tableau, Python, and Spark
Introduction to Data Science
SQL Essential Training
I, hereby, declare that the aforementioned information is true to my knowledge and experience.
Dr Reju Sam John