
Pharmaceutical company.
Senior Scientist II, ML Expert - Pharmacology (Drug Discovery) at AbbVie
About the role
Purpose
This position brings an opportunity to make innovative contributions that will define how Abb Vie leverages AI-enabled drug discovery across our small molecule portfolio. The key responsibilities of this position are to identify, develop, optimize, validate, and deploy innovative machine learning approaches to guide molecular optimization. This role will collaborate closely with project teams comprising medicinal chemists, structural biologists, biochemists, cell biologists, and other computational chemistry / chemoinformatics experts.
Responsibilities
- Consult with project team to establish quantitative targets for driving optimization.
- Identify suitable models to predict small molecule binding affinities for protein targets, and to predict pharmacological properties (PK parameters, etc.).
- Build predictive models for each project endpoint, and carefully benchmarking to evaluate performance and domain of applicability for each model.
- Decisively identify the model that should be used for each project team query molecule, using data-driven approaches that take account of model uncertainty and heteroscedasticity.
- Clearly communicate to the project team the rationale for model selection and why the selected models are best suited for the task at hand.
- Deploy models to ensure accessibility for the project team, facilitating collaborative ideation and optimization.
Qualifications
- Bachelor’s Degree or equivalent education and typically 12+ years of industry experience, Master’s Degree or equivalent education and typically 10+ years of industry experience, PhD and typically 4+ years of industry experience.
- Expertise with developing, implementing and deploying programs and computational solutions employing Machine Learning/Deep learning and Cheminformatics.
- Expertise in AI/ML-enabled molecular generation, pose prediction, affinity prediction and/or prediction of pharmacological properties (e.g. PK).
- Strong programming skills in Python and experience with data science stack including numpy, pandas, scikit-learn, and other related scientific libraries.
- Ability to implement, debug, and maintain computational tools in common programming languages (Python, etc…) and proficiency with cloud computing capabilities.
- Familiarity with modern deep learning architectures including GNN, CNN, RNN, Transformer, GCNN and MPNN, and machine learning paradigms such as generative models, GAN, and active learning.
- Strong analytical and problem-solving skills with demonstrated ability to think critically and creatively, and provide solutions both individually and collaboratively with internal experts.
- Excellent ability to communicate clearly and concisely with colleagues and collaborators including an ability to explain complex ideas to non-specialists.
Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law:
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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.
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We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees.
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This job is eligible to participate in our long-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.
Abb Vie is an equal opportunity employer and is committed to operating with integrity, driving innovation, transforming lives and serving our community. Equal Opportunity Employer/Veterans/Disabled.
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
About Abb Vie
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 including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at www.abbvie.com. Follow @abbvie on LinkedIn, Facebook, Instagram, X and YouTube.
Required skills
Machine learning
Predictive modeling
Model validation
Uncertainty estimation
Drug discovery
Chemoinformatics
Pharmacology
Model deployment
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About AbbVie

AbbVie
PublicPharmaceutical company.
10,001+
Employees
North Chicago
Headquarters
$200B
Valuation
Reviews
10 reviews
3.6
10 reviews
Work-life balance
3.2
Compensation
4.1
Culture
4.0
Career
2.8
Management
2.9
68%
Recommend to a friend
Pros
Great benefits
Good compensation/salary
Flexible work arrangements
Cons
Heavy workload/long hours
Limited career advancement
Poor management/lack of direction
Salary Ranges
88 data points
Junior/L3
Mid/L4
Senior/L5
Staff/L6
Intern
Senior
Director
Junior/L3 · Clinical Data Scientist - Centralized Monitoring & TA Analytics
1 reports
$123,500
total per year
Base
$95,000
Stock
-
Bonus
-
$123,500
$123,500
Interview experience
4 interviews
Difficulty
3.0
/ 5
Duration
14-28 weeks
Experience
Positive 0%
Neutral 25%
Negative 75%
Interview process
1
Application Review
2
HR Screen
3
Hiring Manager Interview
4
Panel Interview
5
Offer
Common questions
Behavioral/STAR
Past Experience
Culture Fit
Technical Knowledge
Latest updates
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