Senior Scientist I/II, Genomics Data Science

Full time

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Employment Information

Job levelSenior level

Salary$91 500 - $173 500

IndustryPharmaceutical Manufacturing

Experience

LocationNorth Chicago, IL, United States

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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 Twitter, Facebook, Instagram, YouTube and LinkedIn.

Job Description

We are seeking a highly motivated and experienced data scientist to join the Bioinformatics team within the Genomics Research Center (GRC). AbbVie’s GRC is a center of excellence for bioinformatics, functional genomics, and human genetics. The GRC works across all R&D including discovery and clinical development, supporting all of AbbVie’s therapeutic areas and multiple other functions such as process sciences, global epidemiology, search and evaluation, and corporate strategy . Our team is dedicated to identifying and interpreting genetic signal at the scale of thousands of phenotypes and millions of individuals, making the knowledge gleaned from genetics accessible to AbbVie’s R&D community, and using data science and machine learning to maximize the value genetics brings to AbbVie.

The ideal candidate will cover the growing responsibilities of this team, including statistical and machine learning analysis in large biobank studies with over 1 million genomes, and integration of genetics and real-world data for drug target identification, disease risk assessment and patient stratification. The candidate should be familiar with developing and improving data analysis workflows on large genetic data, and contemporary data visualization methods. Candidates with a track record of innovative methods development and applications of human genetics in biotech and/or pharma are preferred.

Key Responsibilities:

Provide analysis support for ongoing collaborations seeking to develop and improve processes for development and manufacturing of novel therapeutics using genetic data.
Work closely with scientific teams to analyze genetic data in large biobanks, effectively communicate results to an audience with a wide range of backgrounds and expertise. Work toward making genetics knowledge more accessible through development and maintenance of tools and databases.
Identify methodological problems and devise and implement creative new solutions for the integration of genetics and real-world data.
Keep up with latest literature in methodology and databases for genetic associations.
Work with bioinformatics engineers to optimize newly developed software into reproducible workflows executable by other bioinformaticians, and train other scientists on analysis workflow you have developed.
Present research at external conferences and work toward both independent and collaborative publications.

Significant Work Activities -Continuous sitting for prolonged periods (more than 2 consecutive hours in an 8 hour day)

Qualifications

The level is commensurate with experience.

Basic

PhD in Statistical Genetics, Biostatistics, Biomedical Informatics, Computer Science, Bioinformatics, or closely related field, with expertise in method development and practical application.
Demonstrate ability to develop and execute custom computational analysis plans leveraging novel algorithms and relevant databases.
Ability to summarize analytical results and derive biological/clinical interpretation with genetic data.
Experience in database management in SQL, SQLite, or MongoDB.
Strong written and verbal communication skills.
Fluency in one or more or relevant programming languages, such as R, Python, Java, or C/C++.
Proficiency in a Unix environment and high-performance distributed computing.

Preferred Qualifications:

Expertise in advanced statistical models, interpretable machine learning, or deep learning.
Demonstrated research capabilities include independent work, such as multi-trait Genome-Wide Association Studies (GWAS), Phenome-Wide Association Studies (PheWAS) in biobanks, investigation of co-morbidities, and utilization of Electronic Health Record (EHR) data.
Experience using and/or comparing commonly used methods in genetics/genomics (e.g., genotyping data, whole exome sequencing, whole genome sequencing).
Experience comparing or developing computationally efficient algorithms for large-scale data analysis.
Proven track record of innovation, teamwork, adaptability, initiative, and integrity.

Key AbbVie Competencies:

Builds strong relationships with peers and cross functionally with partners outside of the team to enable higher performance.
Learns fast, grasps the “essence” and can change the course quickly where indicated.
Raises the bar and is never satisfied with the status quo.
Creates a learning environment, open to suggestions and experimentation for improvement.
Embraces the ideas of others, nurtures innovation and manages innovation to reality.

Key Leadership Competencies:

Builds strong relationships with peers and cross-functionally with partners outside of team to enable higher performance.
Learns fast, grasps the “essence” and can change course quickly where indicated.
Raises the bar and is never satisfied with the status quo.
Creates a learning environment, open to suggestions and experimentation for improvement.
Embraces the ideas of others, nurtures innovation and manages innovation to reality

Additional Information

AbbVie 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.