Title : Research Scientist II

Duration : 6 months

Location : Lexington, MA - onsite 5 days/wk.

TOP 3 SKILLS :

1. Patient endotype discovery using unsupervised/supervised ML approaches

2. Omics analysis (primarily proteomics, Olink, Soma, LC-MS) incl differential expression, clinical characterization, clinical outcomes and pathway analyses

3. Experience with CDISC format (as my main work currently is on our RCT data)

Job Description:

The Position

We are seeking a highly motivated Senior Research Scientist to play a key role in supporting our Therapeutic Areas (TA) in their efforts to better characterize patients/diseases in a real-world context. Focused initially on heart failure (HF), you will be responsible for :

(1) using patient-derived molecular and phenotypic data to identify treatment-relevant disease subgroups,

(2) integrating diverse features from Client clinical trials and externally sourced patient cohorts to define novel endotypes and provide real-world context to our novel drug targets, and

(3) utilize modern machine-learning methods to derive and communicate insights to non-expert stakeholders in a clear and meaningful way.

In this role you will:

Develop and apply advanced but explainable AI/ML methods and statistical models to cardiovascular disease

Collaborate with cross-functional teams across EVP areas to identify and validate new endotypes, biomarkers, and drug targets

Analyze large patient-derived molecular and phenotypic datasets, to identify patterns and trends that can inform future target discovery and development

Present findings with clarity and objectivity in internal presentations and publications in scientific journals

Mentor junior scientists and provide guidance on computational methods and analyses as well as identify and drive new internal and external collaborative opportunities.

Qualifications:

• Master's degree in Bioinformatics, Computational Biology, Computer Science / Machine Learning, Genomics, or related field (PhD candidates will be considered w/min of 1 yr prof exp)

• 3+ years working/professional experience

Our ideal candidate meets the following criteria:

• Has proven track record of delivering cohort analyses and clear interpretation of insights derived from machine learning

• Has strong knowledge of machine learning algorithms and their application to biomedical data

• Has experience with programming languages such as Python or R, version control, and high-performance computing

• Has excellent communication and collaboration skills

• Has the ability to work independently and drive projects forward