We are looking for a creative, innovative, intellectually curious and entrepreneurial Data Scientist with experience in developing Machine Learning software to join our Plymouth Meeting (PA) team.
This is an exciting opportunity to work in one of the world's leading human data science teams working with real world insights to help our clients answer specific questions globally, make more informed decisions and deliver results.
We are looking for a Data Scientist who is keen to build data engineering and machine learning tools and products at the cutting-edge of life sciences. The primary focus of the role is to develop ML solutions on high scale-high complexity rich medical data to predict answers to healthcare challenges.
Ideally you will have:
- Postgraduate degree or higher involving machine learning or computer science
- Experience of statistical / machine learning projects in academia or commercial sector end to end with proven delivery capability including capturing requirements, designing analysis plans, interfacing with clients and report / manuscript writing.
- Experience developing scalable solutions and pipelines to handle large and complex data.
- Excellent knowledge of supervised machine learning methods, such as regularized regressions, ensemble tree classifiers (e.g. xgboost), support vector machines, deep learning methods, etc. Good grasp of classical statistical methods, such as fitting regression models, inference testing and sampling.
- Strong programming skills in Python. Experience in pySpark is highly beneficial.
- Solid understanding of best coding practices and version control software such as Git, ability to write clean and efficient code and a good understanding of the data science package landscape.
- Familiarity with agile software development practices such as scrum.
- Excellent written and spoken communication skills, including ability to present technical concepts to lay audiences, write analysis plans for projects, contribute to proposals / grant applications, pitch ideas effectively and persuasively to clients / internal stakeholders, etc.
- A proactive, innovative and pragmatic approach to problem solving and an ability to think critically and independently, able to work as part of a cross-functional team.
Bonus points for:
- Peer-reviewed publications involving machine learning
- Knowledge of healthcare patient-level data.
- Knowledge of epidemiology / biostatistics, particularly analytical issues relating to studies of treatment effectiveness, disease progression, adherence, healthcare utilization, etc.
- Work in bioinformatics.
- Knowledge of healthcare / life science issues involving Real-World Evidence
- Experience with patient-level, longitudinal data.