Senior Scientist II, Computational Biology and Machine Learning (24217-U-670-CBIO)

As a Senior Scientist II, Computational Biology and Machine Learning at Arsenal Biosciences, you will design and implement advanced machine learning architectures using extensive single-cell datasets. You will collaborate closely with experimental scientists to create effective data processing strategies and optimize model performance for drug discovery applications. Additionally, you will have the opportunity to train and mentor a team of ML scientists and engineers while publishing and presenting your findings at academic conferences.

To qualify for the Senior Scientist II, Computational Biology and Machine Learning position at Arsenal Biosciences, you need a Ph.D. in a relevant field like Computer Science, Biomedical Engineering, or Bioinformatics, along with at least 4 years of industry experience. Alternatively, a Master's degree with 9+ years of experience is also acceptable. A strong background in developing deep-learning models related to biology, familiarity with single-cell sequencing data, and robust software engineering skills in Python are essential.

Arsenal Biosciences is committed to employee growth and professional development. As a Senior Scientist II, you will have ample opportunities to mentor junior scientists, participate in conferences, and lead innovative projects that contribute to your field. The collaborative environment encourages knowledge-sharing, enabling you to learn from experts across multiple scientific disciplines.

Arsenal Biosciences offers a comprehensive benefits package for all employees, including medical, dental, and vision coverage, mental health resources, and flexible work schedules. Employees also receive additional 'Arsenal Days of Rest' every quarter to recharge. The company takes pride in its people-first culture and diversity, ensuring a supportive environment for career growth and personal well-being.

Arsenal Biosciences stands out as an employer for a Senior Scientist II because of its dedication to innovation in cancer treatment and the importance it places on collaboration. The company engenders a vibrant culture where diversity is celebrated, fostering creativity and discovery. This role not only allows you to contribute to groundbreaking therapies but also to work alongside some of the brightest minds in the field while making a meaningful impact on patient lives.

In preparing for this question, highlight specific projects where you've successfully implemented machine learning techniques in biomedical contexts. Discuss how you approached the problem, the methodologies you used, and the results or improvements achieved. Highlight your understanding of how machine learning can address complex biological questions.

When answering this question, provide a concise overview of the project, the specific challenges encountered, and how you resolved them. Emphasize your analytical skills, your ability to work with large datasets, and any multi-disciplinary collaboration involved in overcoming these challenges.

To answer this question effectively, discuss your communication strategy and approach to team dynamics. Mention specific instances where you facilitated information exchange, contributed to experimental designs, or adapted your models based on feedback from experimental scientists. Emphasize the importance of understanding their workflow and how your role supports their goals.

Outline the techniques you are familiar with, such as hyperparameter tuning, regularization methods, and cross-validation. Provide examples of how you've applied these techniques in past projects and highlights resulting improvements in model performance and real-world applicability.

In your response, discuss your philosophy for mentorship, mentioning your commitment to fostering an inclusive and supportive environment. Highlight specific strategies such as regular one-on-one meetings, tailored training sessions, and providing opportunities for hands-on experience and involvement in high-impact projects.

When discussing your experience, share specific libraries you are proficient in, such as TensorFlow or PyTorch. Talk about relevant projects where you used these tools, demonstrating your coding skills and the successful application of your models in solving biological problems.

Highlight your ability to convey complex concepts in an understandable way. Provide an example involving a presentation to stakeholders or a non-technical audience where you successfully tailored your message and made the data engaging, illustrating your communication skills.

Emphasize your commitment to continuous learning through various channels, such as attending workshops, participating in online courses, reading relevant journals, and engaging in professional networks. Highlight how staying current helps you bring innovative solutions to your projects.

Discuss the significance of effective data processing in achieving optimal model performance. Explain methodologies you apply, such as normalization, feature selection, or preprocessing techniques, and how you adapt these methods based on project requirements.

Convey your passion for Arsenal Biosciences' mission and commitment to innovative cancer therapies. Discuss how your values align with the company’s focus on diversity, collaboration, and utilizing cutting-edge technology to contribute to meaningful advancements in healthcare.