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I am a highly accomplished research data scientist with more than six years of experience in machine learning, data analytics, and data management. I enjoy turning complex datasets into actionable insights, building robust models, and collaborating across disciplines to advance scientific discovery. Currently, I lead a collaborative project between the University of Canterbury and Purdue University, applying computational methods to smart energy materials. I thrive in interdisciplinary settings, continuously learning new tools (Python, SQL, Snowflake, Power BI) and sharing knowledge through mentoring, talks, and open science.…I am a highly accomplished research data scientist with more than six years of experience in machine learning, data analytics, and data management. I enjoy turning complex datasets into actionable insights, building robust models, and collaborating across disciplines to advance scientific discovery. Currently, I lead a collaborative project between the University of Canterbury and Purdue University, applying computational methods to smart energy materials. I thrive in interdisciplinary settings, continuously learning new tools (Python, SQL, Snowflake, Power BI) and sharing knowledge through mentoring, talks, and open science.

Bushra Anam

Data Scientist, Full Stack Developer, Back-End Developer, +2

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I am a highly accomplished research data scientist with more than six years of experience in machine learning, data analytics, and data management. I enjoy turning complex datasets into actionable insights, building robust models, and collaborating across disciplines to advance scientific discovery. Currently, I lead a collaborative project between the University of Canterbury and Purdue University, applying computational methods to smart energy materials. I thrive in interdisciplinary settings, continuously learning new tools (Python, SQL, Snowflake, Power BI) and sharing knowledge through mentoring, talks, and open science.…I am a highly accomplished research data scientist with more than six years of experience in machine learning, data analytics, and data management. I enjoy turning complex datasets into actionable insights, building robust models, and collaborating across disciplines to advance scientific discovery. Currently, I lead a collaborative project between the University of Canterbury and Purdue University, applying computational methods to smart energy materials. I thrive in interdisciplinary settings, continuously learning new tools (Python, SQL, Snowflake, Power BI) and sharing knowledge through mentoring, talks, and open science.

Available to hire

I am a highly accomplished research data scientist with more than six years of experience in machine learning, data analytics, and data management. I enjoy turning complex datasets into actionable insights, building robust models, and collaborating across disciplines to advance scientific discovery.

Currently, I lead a collaborative project between the University of Canterbury and Purdue University, applying computational methods to smart energy materials. I thrive in interdisciplinary settings, continuously learning new tools (Python, SQL, Snowflake, Power BI) and sharing knowledge through mentoring, talks, and open science.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Fluent

Work Experience

Research Data Scientist at University of Canterbury, NZ

July 1, 2021 - Present

Led a Canterbury University and Purdue University Marsden project on aging and fatigue of smart energy materials. Developed a CNN model to predict material lifespan and analyzed large datasets (over 50,000 records) to examine properties such as conductivity and domain walls. Created and optimized Python scripts for simulations and data analysis using libraries such as Statsmodels, Scikit-learn, TensorFlow, SciPy, Seaborn, and Jupyter. Performed statistical analyses and generated visualizations to categorize materials by durability and performance.

Computational Physicist at University of Auckland / MacDiarmid Institute, NZ

April 1, 2018 - June 1, 2021

Predicted novel 2D structures of gallium and aluminium with exceptional properties for potential electronics applications. Applied ML and statistical modeling to study material properties of predicted 2D structures and outlined practical applications. Collaborated with interdisciplinary teams to develop a transparent conducting oxide with enhanced properties for commercialization.