Your work will change lives. Including your own.
The Impact You’ll Make
With treatments for hundreds of diseases in our sights, we’ve built a data science team with domain expertise in computer science, bioinformatics, physics, biology, mathematics, applied statistics, and more. We work side-by-side with biologists, oncologists, chemists, software engineers, and many others; together, we develop the tools and methods to turn our experimental data into treatments for pathologies that affect the lives of countless individuals. As a data scientist supporting the development of our industrialized workflows, you’ll work with a highly dynamic team that is focused on improving how we move from ideation through to advanced candidate drugs in a way that accelerates decision-making and automates as much as possible to scale the impact that we can have.
You’ll have access to unbelievable scales of data: we currently run up to 2.2 million experiments each week, our ground-breaking Phenom-1 foundation model, trained on > 1 billion in-house images, and our maps of biology and chemistry that contain > 5 trillion relationships across multiple biological and chemical contexts.
In this role, you will leverage this data as you:
-
Develop methods, metrics, benchmarks, and models to help drive drug discovery in a standardized way.
-
Convert exploratory analysis into production-quality functions that can be incorporated into in-house Python packages and that support at-scale generation of data packages to accelerate decisions on passing programs through internal stage gates.
-
Create and analyze enormous sets of connected data for a variety of programs to learn how best to advance drug discovery in an industrialized way
-
Collaborate with engineering teams to mature your models and analyses and put them into productionized flows
-
Deliver quickly and iteratively, both supporting in-flight programs and building improvements for the long-term in short-lived, agile workstreams
-
Learn to leverage new code packages and data science techniques as needed
Location:
Making Toronto, Canada your home base is ideal, however, we will consider on-site work in our Salt Lake City office as well.
The Team You’ll Join
We are an application-oriented group whose goal is to discover drugs at scale, using the toolkit of computational science in collaboration with our counterparts in other engineering (software and data engineering, laboratory automation), scientific (biology, chemistry, clinical science), and operational (laboratory operations, regulatory affairs) disciplines. We are value-driving - data science at Recursion is not just an accelerating function; it is a core part of our value proposition. As data scientists, we are responsible for showing up as leaders and visionaries, helping to shape how Recursion delivers on our mission. We work on what matters and deliver in timescales of weeks not quarters. We focus on the impact that we are trying to make and the “why” of what we are trying to deliver and are resilient if the “how” of what we are doing needs to change.
The Experience You’ll Need
- 1+ years practical experience applying probability, statistics, and machine learning to real-world datasets in service of academic or business applications and recommendations.
- Strong preference for experience in the field of biosciences (particularly pharmaceuticals) or working on projects that require regular cross-disciplinary collaboration.
- Experience working within a fast-paced interdisciplinary team to solve business-relevant problems and communicating complex concepts and methods to audiences with diverse technical backgrounds.
- High fluency with the Python data stack (numpy, pandas, scikit-learn, etc).
- Experience in collaborative data product development and peer code review, including version control tools like git.
- Experience developing, releasing, and maintaining data products in a continuous-use production environment.
- Nice to have: experience in creating compelling visualizations of high-dimensional data that enable clear decision-making and interpretation, prompt engineering for LLMs, cheminformatics, OR analysis of RNA sequencing data.
How You’ll be Supported
- You will be assigned a peer trail guide to support you as you onboard and get familiar with Recursion systems
- Receive real-time feedback on code quality and best practices from a team of peer experts
- Ability to participate and learn from your colleagues in our regular all-hands, journal club & tech talks for Data Science
- Option to attend conferences to learn more from colleagues, networks, and more to better your skillset
#LI-EP1
The Values That We Hope You Share:
-
We Care: We care about our drug candidates, our Recursionauts, their families, each other, our communities, the patients we aim to serve and their loved ones. We also care about our work.
-
We Learn: Learning from the diverse perspectives of our fellow Recursionauts, and from failure, is an essential part of how we make progress.
-
We Deliver: We are unapologetic that our expectations for delivery are extraordinarily high. There is urgency to our existence: we sprint at maximum engagement, making time and space to recover.
-
Act Boldly with Integrity: No company changes the world or reinvents an industry without being bold. It must be balanced; not by timidity, but by doing the right thing even when no one is looking.
-
We are One Recursion: We operate with a 'company first, team second' mentality. Our success comes from working as one interdisciplinary team.
Recursion spends time and energy connecting every aspect of work to these values. They aren’t static, but regularly discussed and questioned because we make decisions rooted in those values in our day-to-day work. You can read more about our values and how we live them every day here.
More About Recursion
Recursion is a clinical stage TechBio company leading the space by decoding biology to industrialize drug discovery. Enabling its mission is the Recursion OS, a platform built across diverse technologies that continuously expands one of the world’s largest proprietary biological and chemical datasets. Recursion leverages sophisticated machine-learning algorithms to distill from its dataset a collection of trillions of searchable relationships across biology and chemistry unconstrained by human bias. By commanding massive experimental scale — up to millions of wet lab experiments weekly — and massive computational scale — owning and operating one of the most powerful supercomputers in the world, Recursion is uniting technology, biology and chemistry to advance the future of medicine.
Recursion is headquartered in Salt Lake City, where it is a founding member of BioHive, the Utah life sciences industry collective. Recursion also has offices in London, Toronto, Montreal and the San Francisco Bay Area. Learn more at www.Recursion.com, or connect on X (formerly Twitter) and LinkedIn.
Recursion is an Equal Opportunity Employer that values diversity and inclusion. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected under applicable federal, state, local, or provincial human rights legislation.
Recursion welcomes and encourages applications from people with disabilities. Accommodations are available on request for candidates taking part in all aspects of the selection process.
Recruitment & Staffing Agencies: Recursion Pharmaceuticals and its affiliate companies do not accept resumes from any source other than candidates. The submission of resumes by recruitment or staffing agencies to Recursion or its employees is strictly prohibited unless contacted directly by Recursion’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Recursion, and Recursion will not owe any referral or other fees. Our team will communicate directly with candidates who are not represented by an agent or intermediary unless otherwise agreed to prior to interviewing for the job.