Senior Data Scientist
Career Path: AgileData
Type: Full Time preferred
Seniority: Mid senior level
Location: Cambridge or MetroWest, MA or New York, New Jersey
- Established computational biology or data science experience in the life sciences domain.
You are intrinsically curious…you’re not afraid to brainstorm new ideas that challenge the status quo…you value working and collaborating with sincere scientific colleagues
You know how to move data around and integrate and visualize it; Strong background/experience with ETL, data mining, statistical analysis, data processing with very large amounts of data
You have intimate knowledge of challenge structured, semi-structured, and unstructured data use cases
Big, undefined problems and petabytes don’t frighten you, rather, they inspire you, and you can’t imagine your career moving in any other direction but into the eye of these challenging but rewarding problems
Extensive experience with algorithms and data processing.
Strong statistical programming skills (Python, R, Perl).
Experience analyzing medical, genomic, biological or chemical information.
Experience with large multivariate data sets, NLP and machine learning.
A PhD in computer science, computational biology, computational chemistry, bioinformatics or related computational science discipline is preferred. Highly experienced candidates with a relevant MS or MBA degree are also preferred.Experience
A minimum of 10+ years industry/consulting or relevant academic experience is required.Description
We are building the next generation of big data and decision support tools to optimize the efficiency and efficacy of research and development.
In this mission critical role, you will define the technical vision and strategic direction for next-generation data science efforts, optimizing existing approaches as well as cultivating durable big data, IoT/real-time, and scientific data science architectures. This position requires a candidate with a well-established and demonstrable track record of harvesting complex research use cases and converting them into powerful and flexible solutions comprising an effective composite of sourced and internally developed software and infrastructure.
The end game is an efficient big data enterprise architecture and tool suite that empowers research scientists to efficiently accomplish collaborative data science and decision making across the R&D pipeline, irrespective of the difficulty of the use case. This requires a flexible architecture and fluid tool suite for any and all combinations of structured, semi-structured, and unstructured data related to a variety of research related disciplines such as genomics, target validation, network medicine, and candidate discovery, as well as development related disciplines such translational medicine, competitive intelligence, trial design, safety, and health outcomes analysis.
- Define and lead a bold agenda around the use of data in new creative ways and develop the architectures and tools that allow data scientists to reduce it to common practice
- Lead, influence, and mentor data scientists and software engineers within a cross-functional environment
- Work with multiple, complex data sources at large scale
- Influence big data and machine learning efforts to build predictive models and identify new data sources/patterns that add significant signal to predictive modeling capabilities. Apply a broad array of skills spanning machine learning, biostatistics, mathematics, modeling, simulation, text-mining/NLP, data-mining, pathway/network analysis
- Communicate and champion strategic, long-range, and capital proposal and usage plans with high-level management in IT, finance, business-line, and strategy functions
- Use advanced visualization tools such as Spotfire, Tableau or similar applications.
- Investigate complex data structures, perform statistical data analysis, standardization and multivariate data analyses and report conclusions.
Senior Data Scientist
Submit CV now.
Arrayo is an Equal Employment Opportunity employer and as such does not discriminate against any applicant for employment or employee on the basis of race, color, religious creed, gender, age, marital status, sexual orientation, national origin, disability, veteran status or any other classification protected by applicable discrimination laws.