Data Scientist II, Deep Learning & Image Analysis

Data Scientist II, Deep Learning & Image Analysis

The Allen Institute accelerates science for a healthier world through large-scale research designed to answer some of the most complex questions in biology. Our multi-disciplinary teams generate foundational knowledge, tools, and data to understand how our brain, cells, and immune system work. We share our work openly so others can build on it, move faster, and ask bigger questions. We drive discovery forward and create new possibilities for improving human health.

The goal of our Cell Science accelerator is to create the first holistic framework to predict how cells self-organize into complex cell communities and tissues in order to program an entirely new kind of synthetic tissue that can be used to ask focused questions about how cells behave, including in response to drug interventions.

The Computational Cell Science team develops scalable, quantitative image-based frameworks for analyzing cell organization, activity, and function. As a Data Scientist I specializing in computer vision, you will work alongside experimental and computational scientists, developing and implementing machine learning and deep learning methods for 3D timelapse microscopy images and owning defined components of the analysis pipeline end to end. Technical decisions within those components are yours, with guidance from senior team members on scope and direction.

The role sits where microscopy, stem cell biology, machine learning, and scientific software meet daily. You will work with large-scale microscopy datasets, applying and adapting state-of-the-art models on dedicated HPC computing infrastructure. What the team builds is released openly and used by researchers outside the Institute.

At the Allen Institute, we believe that science is for everyone – and should be open to everyone. We are dedicated to combating biases and reducing barriers to STEM careers more broadly.

We also believe that science is better when it includes different perspectives and voices. We strive to make the Allen Institute a place where everyone feels like they belong and are empowered to do their best work in a supportive environment.

We are an equal-opportunity employer and strongly encourage people from all backgrounds to apply for our open positions.

Essential Functions

• Design and implement ML/DL pipelines for microscopy image analysis, in collaboration with senior data engineers and scientists
• Preprocess and clean large-scale microscopy datasets, ensuring data quality and integrity for downstream analysis
• Develop, optimize, and fine-tune models, from classical algorithms through DL architectures, for standard image processing tasks such as segmentation, feature extraction, and classification
• Integrate and scale image analysis protocols into high-throughput computational pipelines, working with cross-functional teams
• Participate in code reviews and contribute to efficient, maintainable, well-documented codebases
• Maintain reproducible analysis records; version-controlled code, documented parameters, traceable results, and coordinate with experimental scientists on data collection and study design
• Track developments in machine learning and image analysis and evaluate promising methods against our data
• Adherence to SOPs, GLPs and regulatory requirements

Note: Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. This description reflects management’s assignment of essential functions; it does not proscribe or restrict the tasks that may be assigned.

Required Education and Experience

• Bachelor's degree in computer science, engineering, physics, data science, computational biology, or a related quantitative field
• 1+ year of relevant experience
• Demonstrated experience developing ML/DL models for segmentation, classification, or feature extraction; from research, internship, coursework, or professional work
• Proficiency in Python, including scientific and data manipulation libraries (e.g. NumPy, scikit-image)
• Working experience with a deep learning framework such as PyTorch or TensorFlow

Preferred Education and Experience

• Master’s degree with 2+ years of relevant experience in computer science, engineering, physics, data science, computational biology, or a related quantitative field; or a Bachelor's degree with 4+ years of relevant experience in one of these fields
• Experience with microscopy image data, particularly 3D or timelapse
• Experience with classical machine learning methods (e.g. SVM, random forests) alongside deep learning approaches
• Experience developing or contributing to open-source scientific tools or packages
• Familiarity with software engineering practice: version control with Git, testing, code review, and reproducible build or environment management
• Experience running analyses on HPC or distributed computing infrastructure
• Experience working in a multidisciplinary research environment spanning computational and experimental work

Physical Demands

• Fine motor movements in fingers/hands to operate computers and other office equipment

Position Type/Expected Hours of Work

• This role is currently working onsite and is expected to work onsite for the majority of working hours. The primary work location for this role is 615 Westlake Ave N., with the flexibility to work remotely on a limited basis.

Additional Comments

• **Please note, this opportunity does not offer relocation assistance**
• **Please note, this opportunity does not offer work visa sponsorship**

Annualized Salary Range

$112,950 - $139,750 *

* Final salary depends on the required education for the role, experience, level of skills relevant to the role, and work location, where applicable.

Benefits

• Employees (and their families) are eligible to enroll in benefits per eligibility rules outlined in the Allen Institute’s Benefits Guide. These benefits include medical, dental, vision, and basic life insurance. Employees are also eligible to enroll in the Allen Institute’s 401k plan. Paid time off is also available as outlined in the Allen Institutes Benefits Guide. Details on the Allen Institute’s benefits offering are located at the following link to the Benefits Guide:

It is the policy of the Allen Institute to provide equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, the Allen Institute will provide reasonable accommodations for qualified individuals with disabilities