GSK - Data Scientist - Analytics/Artificial Intelligence - Product Management (8-13 yrs)
GSK is one of the world's foremost pharmaceutical and healthcare companies, and we are proud to be part of an industry that improves the lives of others. We are embarking on a significant transformation journey that will support GSK in becoming a top-quartile data-enabled organisation.
This is an exciting time to join GSK. Given the increased focus on data and analytics and the need to ensure we have a comprehensive strategy that is aligned to the Vaccines business, a role of Sr. Data Scientist is created.
The development of best-in-industry Data capabilities is critical to our ambition to be most innovative Vaccines company. Combining various data streams and providing data near real-time data and visualizations are key component to achieve our ambitions
Vx Tech strive to deliver products and services to Vx business that meet the needs of the business whilst being intuitive, efficient, effective and satisfying to use. We require a skilled Data Scientist focusing on AI/ML specialties, to join our Product Family Team.
This role will provide YOU the opportunity to lead key activities to progress YOUR career. These responsibilities include some of the following.
- Data Scientist is accountable for delivery of various AI/ML capabilities and projects including business as usual operations for Vx tech organization. He / She needs to ensure that they are focused on delivering value at optimal cost while ensuring that GSK Tech is looking far enough into the future to guide the business.
- Accountable for the all the business process identified in the scope below and contributing to the development of AI/ML capabilities Strategy, Systems and service architecture. Jobholder will collaborate with other functional teams and digital innovation team to ensure the optimal portfolio of applications exists to support the business.
- In the emerging data and analytics world AI/ML plays a key role and the AI/ML specialist must be creative thinker and propose innovative ways to look at problems by using data mining (the process of discovering new patterns from large datasets) approaches on the set of information available. He/She will need to validate their findings using an experimental and iterative approach.
- These approaches involve trial and error and may require multiple cycles, so are best addressed using iterative development methods such as agile or lean.
- Given the broad diversity and significant size of the information used as part of the analysis, assessing the validity of the findings can be challenging and, as such, the chances of misleading results are greater. AI/ML specialist will need to be able to present back their findings to the business by exposing their assumptions and validation work in a way that can be easily understood by their business counterparts.
Business process areas in scope:
- All R&D functions (e.g. TRD, CMC, Computational Science etc.), GIO, Commercial and Medical
- Influence machine learning strategy for a program/project; explores design options to assess efficiency and impact, develop approaches to improve robustness and rigour
- Be a key contributor to the planning and direction of a project and effectively prioritize goals
- Lead discussions at peer review and uses quantitative skills to positively influence decision making
- Effectively explain technical concepts at all levels in the organization, including senior managers/stakeholders
- Lead, or makes major contributions to, improvements in methodology or initiatives to address capability gaps or increase efficiency
- Represent GSK externally to advance technical capability across the Industry
- Identify opportunities to apply the latest advancements in Machine Learning and Artificial Intelligence to the fields of biology, chemistry, and medicine
- Create algorithms to extract information from large, multiparametric data sets
- Deploy your algorithms to production to identify actionable insights from large databases
- Compare results from various methodologies and recommend best techniques to stake holders
- Design, develop and implement analytical solutions using a variety of commercial and open source tools (common tools include Python, R, TensorFlow)
- Develop and embed automated processes for predictive model validation, deployment, and implementation
- Connect and collaborate with subject matter experts in R&D, GIO-Q, Commercial and Medical
- Make impactful contributions to internal discussions on emerging machine learning methodologies
- Educate the organization both from IT and the business perspectives on these new approaches, such as testing hypotheses and statistical validation of results
- Provide thought leadership: facilitate cross-geography fertilization of ideas and implements key principles/best-practices and guidelines across the categories
- Enable the future BI / Analytics infrastructure and self-service model
- Demonstrate a combination of business focus, strong analytical and problem-solving skills and programming knowledge to be able to quickly cycle hypothesis through the discovery phase of the project and excellent written and communications skills to report back the findings in a clear, structured manner.
- We are looking for a Data Scientist and if you have these skills, we would like to speak to you.
- Masters degree or equivalent experience
- 8+ years of experience in any atleast 2 of the AI domains: NLP, NLG, Computer Vision, etc.
- A higher degree in Engineering, Statistics, Data Science, Applied Mathematics, Computer Science, Physics,
- Computational Biology, Computational Chemistry or related quantitative field
- Experience understanding of a programming language such as Python.
- Experience with at least one deep learning framework such as TensorFlow, Keras, or PyTorch
- Experience/Familiarity with standard deep learning algorithms (CNN, LSTM, etc.) Experience with version control practices and tools such as Git
- Experience producing high-quality code, tests, documentation
- The ability to perform work with a high degree of independence in terms of self-management of a large variety of tasks and initiatives regarding Quality
- Strong analytical, organizational, interpersonal, and time management skills
- Excellent communication (written and verbal) and interpersonal skills
- If you have the following characteristics, it would be a plus:
- PhD degree or equivalent experience
- Subject matter expertise with relevant business process.
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