Sr Spclst, Decision Science, Data Science

Job Description

Our IT team operates as a business partner proposing ideas and innovative solutions that enable new organizational capabilities. Our team is a diverse collection of scientists and engineers working towards the same goal enabling and accelerating the next generation of pharmaceutical sciences. We collaborate closely with laboratory and in-silico scientists and other IT colleagues on the value chain to propose and implement innovative solutions that enable new organizational capabilities.

Decision Science is seated within the Data Science and Scientific Informatics (DSSI) team of Research and Development Sciences IT (RaDS-IT. We are responsible for developing and applying techniques for quantitative cost-risk-benefit analysis of complex scenarios in R&D. We deeply engage with stakeholders to understand challenges in real-world processes extract domain knowledge and design solutions. Our solution process involves mathematical modeling of data and processes implemented through efficient and modular computational tools to enhance business intelligence and decision-making capability for our stakeholders.

A successful application will engage with stakeholders to understand and formalize real-world problems; will apply data and/or process modeling techniques to represent problems in computation use methods of dynamical systems Bayesian inference simulation uncertainty quantification and AI/ML; and will be responsible for sustained meaningful engagement with stakeholders to iteratively refine problem understanding/formalization and present results; work with other IT product teams to discover develop and deploy products and tools and work with Business Technology Partners to handle shifting priorities. The position will collaborate with scientists IT product teams and engineers across the entire breadth of the pharmaceutical pipeline from discovery to clinical assessment. The position presents an opportunity to apply cutting-edge mathematical and computational techniques to an emerging field with exciting and impactful applications in drug discovery and development.

Education

• M.A./M.S. or PhD in Applied Mathematics Computer Science Operations Research/Industrial Engineering Data Science Bioinformatics/Informatics Statistics Computational Biology Physics or can demonstrate equivalence qualifications in related fields with some experience in the above domains.

Qualifications

• Theoretical knowledge and practical experience in some of the following domains: constrained optimization database design dynamical systems machine learning Bayesian statistical modeling logic programming.

• Experience in applied mathematics or informatics in a medical healthcare public health and/or pharmaceutical domain.

• Fluency in at least one programming language commonly used in scientific domains e.g. Julia Python MATLAB/Octave R

• Experience interacting with subject matter experts and stakeholders outside the domain of applicants expertise to deliver reports or solutions.

• Demonstrated ability to engage scientists in many fields and a willingness to acquire necessary domain knowledge.

• Manage project schedule communicate with stakeholders and deliver results on a timely basis with a high level of independence and discipline.

• Provide guidance and mentorship for junior employees and collaborators within and outside the organization.

• Identify opportunities for methodological innovations and execute on real problem areas.

• Excellent team player and coordination

• Excellent verbal and written communication skills

Preferred

• Experience with the Julia programming language and relevant package ecosystems (SciML AlgebraicJulia Turing etc.)

• Experience in data/knowledge representation and reasoning e.g. ontologies SQL/NoSQL knowledge graphs/OWL Datalog.

• Experience with process modeling e.g. Petri nets discrete event simulation Resource Task Networks Business Process Modeling Notation.

• Experience in high performance computing GPU computing.

• Publication history in related fields.

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We are proud to be a company that embraces the value of bringing together talented and committed people with diverse experiences perspectives skills and backgrounds. The fastest way to breakthrough innovation is when people with diverse ideas broad experiences backgrounds and skills come together in an inclusive environment. We encourage our colleagues to respectfully challenge one anothers thinking and approach problems collectively.

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U.S. Hybrid Work Model

Effective September 5 2023 employees in office-based positions in the U.S. will be working a Hybrid work consisting of three total days on-site per week Monday - Thursday although the specific days may vary by site or organization with Friday designated as a remote-working day unless business critical tasks require an on-site Hybrid work model does not apply to and daily in-person attendance is required for field-based positions; facility-based manufacturing-based or research-based positions where the work to be performed is located at a Company site; positions covered by a collective-bargaining agreement (unless the agreement provides for hybrid work); or any other position for which the Company has determined the job requirements cannot be reasonably met working remotely. Please note this Hybrid work model guidance also does not apply to roles that have been designated as remote.

The Company is required to provide a reasonable estimate of the salary range for this job in certain states and cities within the United States. Final determinations with respect to salary will take into account a number of factors which may include but not be limited to the primary work location and the chosen candidates relevant skills experience and education.

Expected US salary range:

Available benefits include bonus eligibility long term incentive if applicable health care and other insurance benefits (for employee and family) retirement benefits paid holidays vacation and sick days. A summary of benefits is listed here.

San Francisco Residents Only:We will consider qualified applicants with arrest and conviction records for employment in compliance with the San Francisco Fair Chance Ordinance

Los Angeles Residents Only:We will consider for employment all qualified applicants including those with criminal histories in a manner consistent with the requirements of applicable state and local laws including the City of Los Angeles Fair Chance Initiative for Hiring Ordinance

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