About ALVITUR
ALVITUR Analytics and Data Solutions offers custom data solutions and tailored consulting services to help businesses and organizations unlock the full potential of their data. Specializing in advanced analytics, statistical modeling, and machine learning, ALVITUR provides innovative solutions that are designed to meet the unique needs of each client. Whether it’s building custom data pipelines, creating predictive models, or offering expert guidance on data-driven decision-making, ALVITUR is dedicated to delivering impactful results that drive success and innovation.
Founded in 2024 to solve business problems and improve efficiencies of teams nationwide.
About Me
Isaac Rankin is a statistician and data scientist with a strong foundation in statistical modeling, machine learning, and data visualization. He applies his skills to tackle complex problems across a range of industries, combining technical expertise with innovative and strategic problem-solving. Isaac’s work often involves creating data-driven solutions that are both impactful and efficient, enabling organizations to uncover meaningful insights and make informed decisions.
When he’s not immersed in data, Isaac enjoys spending time outdoors, embracing activities that challenge him both physically and mentally. Whether mountain biking rugged trails, cycling scenic routes, playing a competitive round of disc golf, or skiing through snowy landscapes in the winter, he finds balance and inspiration in nature.
Education
2023-2024
MSc Statistical Science (Distinction)
University of Oxford
The dissertation explored generative models for structure-based drug design, investigating innovative approaches to molecule generation for in silico pharmaceutical development. Additionally, collaborated on improving the sensitivity of the Python package PoseBusters, as used by the Nobel-winning AlphaFold project, enhancing its ability to identify physically implausible protein-ligand pairs.
2018-2023
BSc Mathematics & Statistics (Distinction)
University of Victoria
Perfect GPA and a 97.5% average course grade.
Highlights include earning two NSERC-funded research awards, writing two published papers, and presenting research on optimal experimental designs for spline regression models, which earned Third Prize at the Canadian Statistics Student Conference.