Work with business analysts and computational scientists to understand and conceptualize the complex, emerging needs of our scientists, whether they are working at the keyboard or the bench.
Collaboratively and pragmatically solve scientific software engineering challenges encountered at the forefront of genomics, particularly those related to the scalable storage, collaborative analysis and interactive visualization of large, multi-omics datasets.
Plan and prioritize complex scientific software projects in conjunction with collaborators, steering committees and other stakeholders.
Lead local and off-shore engineering teams to support your software development efforts.
Effectively communicate strategies, ideas, goals and progress to departmental, cross-functional and senior management.
Contribute to the broader scientific community through open-source software development.
BS or higher in bioinformatics, computer science or related field.
5+ years experience (including any graduate school) developing tools for data analysis. Seniority of position will depend on experience and other factors.
Experience supporting data science activities using FAIR data management and reproducible practices.
Adept at object-oriented programming, with proficiency in R, Python, C++ or Java.
Familiar with a popular high-level language used in data science, such as Python or R.
Expertise in operating on large data, such as data stored in relational and non-relational databases, array stores, HDF5 files or parquet files.
Demonstrated adherence to best practices in software engineering, particularly usability, version control, testing, and appropriate use of abstraction.
Demonstrated ability to lead heterogeneous engineering teams and interface with domain experts and users.
Demonstrated ability to effectively communicate about complex bioinformatics problems to peers, users and leadership.
Biological domain knowledge and basic data analysis skills are desirable but not required.
Familiarity with formal build/release/deploy and continuous integration frameworks (e.g., Jenkins) is a plus.
You are enthusiastic about working in a scientific environment, especially one that is related to drug discovery and development.
You are a quick learner, are curious about new areas and the opportunity to build expertise, and courageously and creatively take initiative to see your ideas implemented.
You are attracted by the challenges of developing software that solves universal problems in bioinformatics.
You are able to perform at a high level in a fast changing and demanding environment.
You are pragmatic about the tradeoffs between features, quality, and timeliness.
ManpowerGroup is an Equal Opportunity Employer (EOE/AA)