Actuarial Fellow utilizes statistical analysis and modeling to assess and manage risk and estimate financial outcomes. Compiles, prepares, and analyzes data to develop statistical models, probability tables, and actuarial studies and evaluate the likelihood and financial impact of various risks. Being an Actuarial Fellow assists with product design and development by analyzing risk groups and calculating appropriate insurance rates, premium levels, and rating systems and structures. Records and tracks accruals, claims, and settlements and prepares documents for input into regulatory filings, financial budgets, forecasts, and other financial projections. Additionally, Actuarial Fellow applies knowledge of mathematics, probability, statistics, principles of finance and business to calculations in life, health, social, and casualty insurance, annuities, and pensions. Requires a bachelor's degree. Requires Fellow of Society of Actuaries (FSA). Typically reports to a manager. To be an Actuarial Fellow typically requires 12+ years of related experience. Achievement and depth of knowledge of specialization or field is the main differentiator. Advisory role on complex and challenging projects and initiatives. Recognized for deep technical and industry knowledge and innovative thinking. Provides thought leadership and guidance to a functional area and the organization. (Copyright 2024 Salary.com)
Recursion
The Recursion Maps of Biology are fully-relatable environments where high-dimensional profiles of genome-wide genetic and chemical profiles generate trillions of relationships between biological perturbations and potential therapeutic interventions. Recursion has developed workflows for conducting inferential discovery of relational insights from biological maps and automated the progression of these insights through the drug discovery process. This involves utilizing standardized, scaled ‘omics technologies and chemical optimization through loops of experimental data and ML predictions while continually exploring technology that can push the bounds of drug discovery.
The Impact You’ll Make
In addition to the technological advancements that power Recursion’s ability to model complex biology across the genome, modern AI and ML capabilities have unlocked powerful tools in extracting causal biology from multimodal patient data. Leveraging these advancements, the Computational Biology Fellow will apply their creative mind to find inventive and unconventional strategies that integrate world-class patient genomics data from industry leaders such as Tempus, with Recursion's scaled and standardized experimental data. To capture the full potential of these data systems, this role will capitalize on existing state-of-the-art in AI and ML while also driving entirely new methodology in this space. We envision that taking on bold approaches to integrating patient and experimental data will reveal a greater understanding of disease biology, causality, and translational biomarkers, and will support the discovery of new, high-impact therapeutic solutions for patients.
The Team You’ll Join
This role is seated within a small, innovation-centric team at Recursion with the mission of entering entirely new frontiers of modeling, understanding and treating disease. It is dedicated to investigating new technologies and ideas that will drastically improve the drug discovery process, focusing on quickly reaching decisive endpoints. In this startup-like environment, you will take on a wide range of scientific responsibilities and join a team of dedicated scientists that all lead change through cross-functional collaboration and direct scientific engagement. You will report to the VP of Industrialized Drug Discovery and join flexible teams based on the projects at hand.
In this role, you will:
Location:
Making one of our offices your home base – Salt Lake City, Toronto, or Montreal – is ideal, however we will consider remote work for this position. We ask that remote employees commit to regular on-site visits for routine work and departmental events.
What You’ll Need
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