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Bristol Myers Squibb: Principal Scientist, Informatics And Predictive Sciences

Bristol Myers Squibb

This is a Full-time position in Seattle, WA posted December 26, 2020.

At Bristol Myers Squibb, we are inspired by a single vision – transforming patients’ lives through science.

In oncology, hematology, immunology and cardiovascular disease – and one of the most diverse and promising pipelines in the industry – each of our passionate colleagues contribute to innovations that drive meaningful change.

We bring a human touch to every treatment we pioneer.

Join us and make a difference.

About Bristol-Myers Squibb Bristol-Myers Squibb is a global Biopharma company committed to a single mission: to discover, develop, and deliver innovative medicines focused on helping millions of patients around the world in disease areas such as oncology, cardiovascular, immunology, fibrosis and neuroscience.

Join us and make a difference.

We hire the best people and provide them with a work environment that places a premium on diversity, integrity, collaboration and personal development.

Through a culture of inclusion, we create a better, more productive work environment.

We believe that the diverse experiences and perspectives of all our employees help to drive innovation and transformative business results.

Job Title Principal Scientist, Informatics and Predictive Sciences Location San Francisco/Cambridge/Seattle/San Diego/Lawrenceville Division Research and Development Direct Manager Tomas Babak Position Summary As Principal Scientist in Informatics and Predictive Sciences you will integrate large-scale biological, biochemical, and structural data to develop patient selection criteria for discovery-stage drug development programs.

You will collaborate with pre-clinical scientists, computational biologists, clinicians, and external research partners to develop and test your predictions.

You will have significant potential to impact the drug development path of BMS assets by ensuring that the patients who can benefit are identified and their personalized disease biology understood.

Direct Reports 1-2 Detailed Position Responsibilities Personalized medicine, where treatment involves taking advantage of a disease feature specific to a set of patients, is emerging as an important path for drug development with distinct advantages and proven clinical benefits.

The obvious requirement is that patients meet the selection criteria which is typically founded in disease biology, and for most indications/diseases, personalized treatment options do not yet exist.

Coincident with an increased focus on personalized drug development has been an explosion in available molecular and clinical data from patients and model systems.

NGS readouts from tens of thousands of patients have enabled a molecular and genetic dissection of many diseases and has been especially useful in defining patient sets with similar disease etiology.

Association with clinical outcomes has revealed novel disease biology while shedding light on potential points of therapeutic intervention.

Pre-clinical model systems have also been more thoroughly characterized and aspects of their outputs likely to translate to the clinic are better understood.

This includes chemical and genetic screening data in cell lines.

Finally, the field of cheminformatics has recently benefited from much improved drug-target interaction prediction methods.

In silico drug screens, for example, are becoming sufficiently accurate to have real-world applications.

At BMS we believe patient-derived data will be key to unlocking personalized treatment opportunities and have made many investments in generating and aggregating these data as part of our clinical trials and through external research collaborations.

We are seeking a collaborative and conscientious scientist to lead prediction of novel patient selection opportunities for our internal and partnered drug development programs.

Potential to engage BMS scientists and academic/industry collaborators from an extensive research network make this a unique and challenging opportunity with genuine potential to make a big impact on the health and wellbeing of patients.

Desired Experience Required: PhD in computational biology/bioinformatics, statistics, computer science/math/engineering or a related field with a firm grasp of quantitative methods 5 years of industry and/or postdoctoral experience Expert proficiency in Python and R/Matlab/SAS Evidence of scientific vigor and application of independently conceived problem solving approaches in publications/conferences Experience integrating and interpreting high-throughput noisy data (e.G.

real-world evidence, GWAS, genomics, protein-drug interactions, biological networks, compound/genetic screens) Expert on: cross-validation, logistic regression, dimension reduction, SQL, data wrangling, benchmarking Experience communicating interpretation of results to both technical and non-technical audiences Working knowledge of cell and molecular biology Ideal Candidates Would Also Have: Passion for developing novel approaches to solve previously untouchable scientific problems Out-of-the box thinking with a deep scepticism for emerging scientific trends Experience in drug discovery, esp.

target ID, patient stratification, and/or patient selection Other Qualifications: Candidates with an extensive machine learning background (e.G.

in physics, computer science, engineering) and no prior experience in biology are also encouraged to apply.

Around the world, we are passionate about making an impact on the lives of patients with serious diseases.

Empowered to apply our individual talents and diverse perspectives in an inclusive culture, our shared values of passion, innovation, urgency, accountability, inclusion and integrity bring out the highest potential of each of our colleagues.

Bristol Myers Squibb recognizes the importance of balance and flexibility in our work environment.

We offer a wide variety of competitive benefits, services and programs that provide our employees with the resources to pursue their goals, both at work and in their personal lives.