Senior Scientist, Machine Learning

Gaithersburg, MD

Are you passionate about being a Senior Scientist specializing in Machine Learning? Do you have expertise in deep learning, generative models, and adversarial networks? Can you leverage your data science skills to advance the boundaries of science and deliver life-changing medicines to patients? We have an exciting opportunity for you at AstraZeneca!

What You’ll Do

This role allows a dedicated and motivated machine learning scientist to develop end-to-end capabilities that will significantly impact the future of biologics drug delivery.

• Collaborate: Work closely with data and drug discovery scientists to develop machine learning methods that optimize biologics design.

• Experiment Design: Identify opportunities in Biologics Engineering where machine learning can inform experiments. Recommend additional data and metadata to enhance model performance.

• Active Learning: Collaborate with machine learning experts in antibody design to implement state-of-the-art techniques in an end-to-end active learning system.

• Grow: Expand your expertise in biologics engineering by learning from leading scientists. Use your combined knowledge in biologics and machine learning to uncover new opportunities for enhancing biologics design.

• Enable: Build and maintain a high level of expertise with the informatics environment of the Biologics Engineering team, training bench scientists on data management and analysis processes, including data quality verification.

• Engage: Foster strategic external collaborations, with opportunities to publish research in prestigious journals and conferences.

• Validate: Support the testing and experimental verification of data analysis tools and pipelines in collaboration with AstraZeneca partners.

• Communicate: Effectively translate complex concepts for non-experts in internal and external scientific meetings.

Education & Experience Requirements:

• PhD or 5 years of equivalent experience in a relevant computational field.

• Hands-on experience with machine learning frameworks and libraries.

Essential Requirements:

• Experience with machine learning methods and their application in molecular biology.

• Proficiency in Python or Rust for analyzing experimental data.

• Strong communication skills and attention to detail; capable of building effective relationships with diverse individuals.

• Proven ability to work collaboratively as part of a team.

• Integrity and commitment to ethical practices.

Desirable for the Role:

• Proven impact demonstrated through publications or contributions to code repositories.

• Experience with active learning, generative models, and Bayesian optimization.

• Understanding of data requirements for modeling biological data using machine learning techniques.

• Experience integrating domain knowledge from biology into machine learning methods.

• Familiarity with antibody discovery processes.

Why AstraZeneca?

At AstraZeneca, we seize opportunities for change, recognizing their potential to drive significant advancements. Our mission to deliver life-changing medicines is fueled by ambition—finding those moments that can lead to extraordinary outcomes. Join us on our journey to redefine what a biopharmaceutical company can be. We are pioneering innovative methods and bringing together diverse teams to achieve our goals.

About Our Gaithersburg Oncology Hub

Our Gaithersburg, Maryland facility creates life-changing medicines for people around the world. This campus employs more than 3,500 experts in our field and is only a short drive from Washington, DC. This modern and vibrant scientific campus is the home of R&D and Oncology in the US. Here, we play host to some of the most cutting-edge technology and lab spaces, all designed to inspire collaboration and cross-functional science. We are dedicated to creating a culture of inclusion and collaboration.

The Gaithersburg site offers a variety of amenities to help keep our employees happy and healthy. This includes a fitness center, employee healthcare clinic, electric vehicle charging stations, dry cleaning, full-service cafeteria and copy center, game rooms, community garden and more. This is where you’ll find newly-designed, activity-based work spaces to suit a variety of working styles while increasing collaboration between teams.

Where can I find out more?

Our social media, Follow AstraZeneca on LinkedIn https://www.linkedin.com/company/1603/

Follow AstraZeneca on Facebook https://www.facebook.com/astrazenecacareers/

Follow AstraZeneca on Instagram https://www.instagram.com/astrazeneca_careers/?hl=en

Competitive remuneration and benefits apply

We offer a competitive Total Reward program including a market driven base salary, bonus and long term incentive. We have a generous paid time off program and a comprehensive benefits package.

AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We follow all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

The annual base pay (or hourly rate of compensation) for this position ranges from $107,244.80 - $160,867.20 USD, either as annual base pay or as the hourly rate (annual base pay divided by 2080 hours)]. Hourly and salaried non-exempt employees will also be paid overtime pay when working qualifying overtime hours. Base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience.  In addition, our positions offer a short-term incentive bonus opportunity; eligibility to participate in our equity-based long-term incentive program (salaried roles), to receive a retirement contribution (hourly roles), and commission payment eligibility (sales roles). Benefits offered included a qualified retirement program [401(k) plan]; paid vacation and holidays; paid leaves; and, health benefits including medical, prescription drug, dental, and vision coverage in accordance with the terms and conditions of the applicable plans. Additional details of participation in these benefit plans will be provided if an employee receives an offer of employment. If hired, employee will be in an “at-will position” and the Company reserves the right to modify base pay (as well as any other discretionary payment or compensation program) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors.

Date Posted

Closing Date