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Senior Data Scientist, Computational Biology & Toxicology

Company Description

AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas – immunology, oncology, neuroscience, and eye care – and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at www.abbvie.com. Follow @abbvie on XFacebookInstagramYouTubeLinkedIn and Tik Tok.

Job Description

The Computational Toxicology group is dedicated to advancing in-silico methods that enhance the prediction and understanding of safety and toxicology for both small and large molecules. Team members will work with diverse biology-related datasets, ranging from pharmacology, toxicology, genomics, and chemistry, applying data science and machine learning techniques. The primary goal is to leverage data effectively and identify useful insights. This role focuses on leveraging computational expertise to process and analyze biological datasets for predictive modeling and novel safety-related discoveries.

Responsibilities:

  • Collaborate with research teams and data scientists to design and implement data-driven strategies, utilizing machine learning/AI methods to support discovery and preclinical safety studies. Work closely with scientists to co-develop tools and solutions tailored to the most relevant and pressing research problems, ensuring that computational approaches align with scientific objectives.
  • Design, develop, and implement solutions with applications including, but not limited to, chemistry, in vitro, preclinical, clinical, and genomic datasets.
  • Identify, curate, and process internal and external biology and safety-related datasets. Apply data science methodologies to harmonize and analyze complex datasets, uncovering associations that inform safety assessments.
  • Develop predictive models, analytical tools, and intuitive user interfaces to translate computational findings into actionable insights, enabling safety risk prediction.
  • Communicate results and methods clearly to both scientific and non-technical audiences, ensuring effective knowledge transfer across teams.

Qualifications

 

  • PhD in Pharmacology, Computer Science, Computational Biology, Statistics, or a related field with experience in biology or toxicology datasets. Industry experience in the pharmaceutical or biotech sector is a plus. Bachelor’s Degree or equivalent education with 10 or more years of experience, Master’s Degree or equivalent education with 8 or more years of experience.
  • Proficiency in bioinformatics and data science tools, with expertise in Python and experience with parallel and/or cloud computing. Familiarity with database management systems and advanced querying techniques for efficiently handling and extracting insights from large datasets.
  • Solid understanding of machine learning techniques, including supervised/unsupervised learning, clustering, classification algorithms (e.g., SVMs, random forests, gradient boosting trees, deep learning), and predictive modeling. Experience with advanced AI techniques, such as generative models (e.g., GANs, VAEs) and large language models (LLMs), is highly desirable
  • Experience in statistical methods, such as hypothesis testing, Bayesian inference, time-series analysis, and multivariate analysis, particularly applied to biological datasets.
  • Experience with data visualization and interface development with an emphasis on biological data representation.

Additional Information

Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law: ​​

  • The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location, and we may ultimately pay more or less than the posted range. This range may be modified in the future.​​

  • We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees.​​

  • This job is eligible to participate in our short-term incentive programs. ​​

​​

Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, incentive, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole and absolute discretion unless and until paid and may be modified at the Company’s sole and absolute discretion, consistent with applicable law. 

AbbVie is an equal opportunity employer and is committed to operating with integrity, driving innovation, transforming lives, serving our community and embracing diversity and inclusion.  It is AbbVie’s policy to employ qualified persons of the greatest ability without discrimination against any employee or applicant for employment because of race, color, religion, national origin, age, sex (including pregnancy), physical or mental disability, medical condition, genetic information, gender identity or expression, sexual orientation, marital status, status as a protected veteran, or any other legally protected group status.

US & Puerto Rico only - to learn more, visit https://www.abbvie.com/join-us/equal-employment-opportunity-employer.html 

US & Puerto Rico applicants seeking a reasonable accommodation, click here to learn more:

https://www.abbvie.com/join-us/reasonable-accommodations.html

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Average salary estimate

$135000 / YEARLY (est.)
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$120000K
$150000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Senior Data Scientist, Computational Biology & Toxicology, AbbVie

At AbbVie, we’re not just about bringing innovative medicines to life; we’re also about building a team that’s passionate about making a difference. As a Senior Data Scientist in Computational Biology & Toxicology based in North Chicago, IL, you'll be at the forefront of enhancing predictive modeling in safety assessments. Your days will be filled with analyzing diverse datasets in pharmacology, genomics, and toxicology while applying advanced machine learning techniques. You’ll collaborate closely with research teams, helping them to design data-driven strategies that truly transform preclinical safety studies. The role demands creativity—designing and implementing analytical tools that translate complex data into actionable insights is key. Plus, you'll be communicating your findings to both technical and non-technical audiences, making sure that your work resonates across the board. If you have a PhD in a relevant field and a knack for navigating biological datasets, your experience in the pharmaceutical or biotech sectors will be highly valued here. Familiarity with AI techniques and a strong foundation in bioinformatics are essential for success in this role. Join us, and let’s work together to advance human health through innovative science!

Frequently Asked Questions (FAQs) for Senior Data Scientist, Computational Biology & Toxicology Role at AbbVie
What are the key responsibilities of a Senior Data Scientist in Computational Biology & Toxicology at AbbVie?

As a Senior Data Scientist specializing in Computational Biology & Toxicology at AbbVie, your responsibilities will involve collaborating with research teams to implement machine learning techniques for safety assessments, designing predictive models, and analyzing complex biological datasets. You’ll focus on the integration of computational solutions with scientific objectives to facilitate drug development processes.

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What qualifications do I need to apply for the Senior Data Scientist position at AbbVie?

To apply for the Senior Data Scientist, Computational Biology & Toxicology role at AbbVie, you should have a PhD in Pharmacology, Computer Science, Computational Biology, Statistics, or a related field, along with relevant industry experience in the pharmaceutical or biotech sectors. Strong proficiency in bioinformatics, Python, and machine learning techniques is also essential.

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How does AbbVie support the development and growth of its Senior Data Scientists?

AbbVie is committed to fostering the growth of its employees, including Senior Data Scientists. This includes providing comprehensive training opportunities, supporting in-depth research collaborations, and encouraging participation in industry conferences to ensure you’re keeping pace with innovations in computational biology and toxicology.

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What types of datasets will I work with as a Senior Data Scientist at AbbVie?

In your role as a Senior Data Scientist in Computational Biology & Toxicology at AbbVie, you'll work with a variety of datasets, including pharmacology, toxicology, genomics, and chemistry datasets. Your expertise will help harmonize and analyze these complex datasets to extract meaningful safety-related insights.

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Can you describe the work environment at AbbVie for Senior Data Scientists?

The work environment for Senior Data Scientists at AbbVie is collaborative and innovative. You will work alongside passionate researchers and data scientists who value communication and knowledge transfer. The team is dedicated to making impactful contributions to public health and encourages a culture of continuous learning and sharing ideas.

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Common Interview Questions for Senior Data Scientist, Computational Biology & Toxicology
Can you explain your experience with machine learning techniques in a biological context?

To effectively answer this question, highlight specific projects where you've applied machine learning to biological datasets. Discuss techniques you've used, such as supervised and unsupervised learning, and how they influenced your research outcomes in the areas of pharmacology or toxicology.

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How do you approach collaboration with biologists and non-technical stakeholders?

Emphasize your communication skills and experience in translating complex data science concepts into understandable insights for non-technical stakeholders. Provide examples of past collaborations and how they led to effective outcomes.

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What statistical methods are you familiar with, and how have you applied them?

Speak to your knowledge of statistical methods such as Bayesian inference and multivariate analysis. Provide examples of how you've applied these methods in your previous research to draw conclusions from biological datasets.

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Describe a time you faced a challenge in a data science project and how you overcame it.

Illustrate a specific challenge, detailing your thought process and the steps you took to resolve it. Focus on problem-solving strategies that demonstrate both technical skills and adaptability.

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What tools and programming languages do you prefer to use in your projects?

Mention specific tools you've used such as Python and any bioinformatics or data science platforms. Explain why you prefer these tools and how they contribute to your efficiency and effectiveness in analyses.

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How do you ensure data integrity and quality in your analysis?

Discuss your approach to validating datasets, including methods for cleansing data, cross-verifying results, and ensuring that data sources meet necessary reliability standards.

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Give an example of a predictive model you’ve developed and its impact.

Share details of a predictive model you've built, focusing on the problem it aimed to solve. Highlight its impact by discussing results achieved and any subsequent influence it had on safety assessments or research direction.

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What experience do you have with data visualization, and why is it important?

Talk about your experience with data visualization tools, explaining how you use them to make complex data more accessible. Share examples of your work that included visual components that enhanced the understanding of your results.

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How do you stay updated with the latest developments in your field?

Highlight how you engage with the professional community, such as attending conferences, participating in journal clubs, or following thought leaders in data science and computational biology. Describe any specific resources you rely on.

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What interests you most about the role of Senior Data Scientist at AbbVie?

Express your passion for working at the intersection of data science and biology, especially in a company like AbbVie that prioritizes innovation in healthcare. Share your desire to make a direct impact on patient safety and outcomes through your work.

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AbbVie’s mission is to discover and deliver innovative medicines that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people’s lives across several key therapeutic areas: i...

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March 19, 2025

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