Staff Data Scientist- Biotech: Boston, MA.

iO Associates are delighted to be supporting this growing biotech organization on the appointment of a Data Scientist in a new headcount role. As a Data Scientist, you will play a crucial role in the development of an innovative platform for advancing the research and development of life-changing medicines. You will have the opportunity to work with a diverse team of data scientists, engineers, and scientists, driven by a shared mission to revolutionize the industry. If you are passionate about leveraging ML and DS to make a meaningful impact on outcomes, we would be keen to hear from you.

Responsibilities:

Propose, design, and develop ML learning approaches using high-dimensional e-health records and data.
Design, develop, and support ML pipelines, workbenches, and dashboards to enable users to solve problems.
Collaborate with multiple stakeholders and cross functional teams to derive user requirements and ensure the relevance and impact of models, analyses, and pipelines.
Develop well-designed, tested, and documented software packages.
Be an active team member in code, design, and analysis review.

Requirements:

Quantitative degree with 7+ years of post-degree experience or equivalent.
Broad experience in ML, including supervised learning, unsupervised learning, dimensionality reduction, clustering, model selection, and feature selection.
Demonstrated experience with ML on e-health records.
Proficiency in Python and experience with machine learning and data science packages.
Experience with MLops methodology, such as workflow orchestration, experiment tracking, containerization, and reproducible research.
Experience with collaborative software development using source control management, unit testing, code review, and continuous integration/continuous deployment.
Experience with big data analytics engines and working in cloud environments.
Experience with statistical methods such as hypothesis testing, longitudinal modeling, and time-to-event analysis.

Preferred Skills:

Experience with analyzing and interpreting data, such as genomics, proteomics, or metabolomics.
Familiarity with various types of data integration and data fusion techniques.
Knowledge of advanced statistical modeling techniques for complex biological or clinical data.
Understanding of drug discovery and development processes, including target identification, lead optimization, and pre-clinical evaluations.
Proficiency in data visualization tools and techniques to effectively communicate scientific findings.
Familiarity with regulatory guidelines and considerations in the pharmaceutical or healthcare industry.
Experience with cloud-based data storage, computing, and distributed computing frameworks.
Knowledge of natural language processing (NLP) and text mining techniques applied to biomedical literature and clinical notes.

Get in touch with Edward on

e.hincks @ioassociates.com