Associate Director, Data Science & Machine Learning
We are seeking an experienced data scientist to leverage data mining techniques, machine learning and other computational methods to identify new ways to treat human diseases. The successful candidate will bring enthusiasm, intellectual curiosity, statistical rigor, a keen interest in the applications of data science and machine learning techniques, and a deep-rooted desire to innovate.
Key Responsibilities
Develop and deploy statistical and computational methods, employing AI/ML where appropriate, to tackle the company's key scientific and therapeutic goals. Be a key visionary and stake holder in our data science and ML strategy to deliver an ambitious and impactful analytical roadmap. Collaborate with the wider informatics team on data science strategy and implementation. Work with a variety of 'omics data sets to characterise cell models, identify novel targets, and assess therapeutic efficacy of small molecular and nucleotide base therapeutics. Help to grow and develop a small team of data scientists and ML engineers to combat some of the more challenging questions in target discovery, drug discovery, and drug development. Work closely with the Human Genetics and Computational Chemistry teams to guide, inform and assist in analyses in these areas. Collaborate with our wet lab scientists on experimental design and hypothesis testing for both wet and dry (in silico) experiments. Present key findings to internal and external stakeholders in a manner targeted towards the intended audience. Collaborate with platform developers and bioinformaticians to define a data storage strategy that is not only ML ready but optimised for data science and data mining applications.
Qualifications and other requirements
Required:
PhD in machine learning, data science, computational biology, or a similar discipline is required. 5+ years of industry experience applying data science/ML techniques to genomics data and/or target discovery. A strong understanding of state-of-the-art data mining and machine learning approaches and their application in solving the central challenges in target identification and drug discovery A track record of mentoring more junior researchers. Ability to conceptualise, implement and evaluate machine learning approaches. A strong understanding of frequentist and/or Bayesian statistics, including data simulation, development of bespoke statistical tests, and de novo hypothesis generation. Experience presenting the complex subject matter to non-expert audiences. Experience working as part of a multidisciplinary team contributing to both short and long-term team goals. High level of proficiency in writing python code or equivalent.
Desirable:
A keen interest in and passion for the evolving landscape of the data science field. Experience working as part of a multidisciplinary team including software developers, platform developers, and/or bioinformaticians. Experience running multiple data science projects at once within an AGILE framework or similar. Experience using version control (git) as part of a larger collaborative project. Experience working with very large datasets, using parallel processing such as CUDA
This is an exciting opportunity for an enthusiastic and ambitious data scientist to a make a huge impact on the way we answer scientific questions and design therapeutics aiming to materially improve the lives of patients.
Insmed provides excellent holiday allowance, health cover, life insurance, equity in the form of stock option, and a collaborative environment where your career will flourish.
This role is hybrid role with a requirement of an onsite presence.
