GSK - Digital Data Scientist - PhD (4-6 yrs)
Job description :
Site Name: Bengaluru Luxor North Tower
GSK's Digital Biomarkers team partners closely with the RW Data Management & Programming team to support drug development and patient access. The team leverages remote technologies such as wearable devices or mobile phones to collect data from patients away from our clinical sites, with the aim to generate objective data that describes the impact of our medicines in patient's everyday lives.
We are an in-house team sitting at the interface of digital technology and data science; our main focus is to support our drug development programmes to ensure our medicines help patients do more, feel better and live longer. A core team activity consists of applying sophisticated algorithms and techniques to tackle complex problems in the analysis of dense timeseries data, and in turn generating value for the development of new medicines.
As a Digital Data Analyst, you will be accountable for the delivery of a portfolio of digital biomarker data science projects across several disease areas. In this role, you will apply your expertise in signal processing, and machine learning to derive solutions to a range of problems in digital sensor data.
- Process, analysis and interpretation of digital biomarker data using common programming languages such as Python.
- Create novel algorithms to extract information from unstructured raw sensor data and other multiparametric data sets captured in Phase I-IV clinical trials.
- Apply signal processing techniques for feature engineering to extract clinically relevant information from digital data.
- Generate and validate machine learning models to identify actionable insights from complex sensor data.
- Connect and collaborate with subject-matter experts in clinical development and other disciplines.
- Make impactful contributions to internal discussions on innovative methodologies to analyse digital data.
- Maintain up to date knowledge on recent advances in data science applicable to digital data (through robust review of scientific literature).
- Adopt good scientific practices in all phases of the research and development process in alignment with the ICH-GCP.
This includes the use of collaborative code development tools (i.e. Git), version control detailed code documentation and quality checking.
Basic qualifications and skills:
- A higher degree in Engineering, Data Science, Statistics, Applied Mathematics, Computer Science, or related discipline.
- Preferably Ph.D. with specialised knowledge in data science applied to digital data
- Ability to work autonomously and collaboratively as part of a team to both teach and learn every day.
- Extensive hands-on experience in scientific computing using common data science packages for Python such as:
Pandas, SciPy, NumPy, SciKit-Learn, PyTorch, TensorFlow, Seaborn/MatplotLib
- Excellent all-round analytical, statistical processing and programming abilities.
- Strong written and verbal communications.
- Experience with Deep Learning would be advantageous.
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