Principal, Data Science and Advance Analytics (gsk)

Job Description

Basic qualification:

• 10+ years of experience of working in Data Science or related role in business / consulting setting

• Hands on technical expertise, with experience in driving analytics solution end-to-end until production

  JOB IS FROM: italents.netVIEW

• 8+ years in applied Machine Learning, NLP, deep learning, reinforcement learning, supervised and unsupervised learning algorithms.

• Solid Understanding and implementation exposure (corporate / learning) generative / GenAI models, Agentic AI frameworks

• Strong programming skills in Python, with experience using relevant libraries (TensorFlow, PyTorch, scikit-learn, etc.)

• Proficiency in SQL, Statistics, data pipelines and data story telling through visualization methods.

• Working knowledge of cloud based and local data science frameworks and toolkits. Experience in Azure / Databricks / Azure Health is preferred but GCP / AWS would be considered.

• Ability to build quick prototype Utilizing modern front-end frameworks (e.g., React, Angular, Vue.js) and back-end technologies (e.g., Python/Flask, Node.js) would be a plus, not mandatory

• Exposure to building large scale machine learning systems or product development environment would be preferred but not mandatory.

• Demonstrate effective oral and written communication, able to deliver convincing, clear presentations to all levels of stakeholders.

• Good knowledge of database management, data reporting and analytics, data visualization for business consumption, understanding of best practices with data structures for analytics and reporting, data manipulation, database and analytics skills to develop insightful measures for actions and decision making in a business setting.

• Experience applying data science to clinical trials operations (study enrolment acceleration, trial site selection, country profiling, recruitment curve prediction etc), patient identification or medical domain a plus/preferred, but not mandatory.

• Demonstrated curiosity and passion about creative problem solving and data innovation, demonstrated accountability in driving project, demonstrated autonomy in leading stakeholder discussions and delivery.

Job Responsibilities:

• Define the data science and analytics strategy and manage the delivery roadmap.

• Consultative problem solving with stakeholders - problem identification, potential solutions; lead execution of innovative and high-value analytics visualizations.

• Implement sound model development methodology that includes clear model quality objectives and quality measurement methods from the onset. Ensure that machine learning models are appropriately trained and tuned for accuracy and relevance with analytical findings within the team. Ensure SDLC principles are followed, and good quality code (ie. Well documented, reusable, bug-free, etc) is delivered.

• Work with a team of Data Scientists and Analysts to manage efficient execution of the strategy and roadmap, using advanced analytics (descriptive / inquisitive / predictive), including hands-on support of all development activities. Develop team members on methodology and advanced analytics approaches with a focus on fostering high morale and motivation.

• Stay on top of the latest external methods and approaches, current and emerging industry trends, and advanced methods/best practices; Pull through expertise through critical deliverables and work as a “player-coach”.

• Appropriately train and maintain machine learning models for accuracy and relevance with analytical findings.  Pull through analytics and business acumen through appropriate selection of methods fit for purpose that reveal customer patterns in the data that may spark additional data analysis or research for deep customer insight.

• Productize analytics solutions / Proof of concepts as features on Azure based analytics platform using systems understanding, engineering constraints and system performance needs.

• Develop compelling summaries that visualize the data through narrative dashboards to clearly tell a succinct story in easy-to-understand ways; Focus on the key findings and insights in alignment with stakeholders' goals/business needs with proper validation techniques to build confidence in the results.

Why GSK?

Uniting science, technology and talent to get ahead of disease together.

GSK is a global biopharma company with a special purpose – to unite science, technology and talent to get ahead of disease together – so we can positively impact the health of billions of people and deliver stronger, more sustainable shareholder returns – as an organisation where people can thrive. We prevent and treat disease with vaccines, specialty and general medicines. We focus on the science of the immune system and the use of new platform and data technologies, investing in four core therapeutic areas (infectious diseases, HIV, respiratory/ immunology and oncology).

Our success absolutely depends on our people. While getting ahead of disease together is about our ambition for patients and shareholders, it’s also about making GSK a place where people can thrive. We want GSK to be a place where people feel inspired, encouraged and challenged to be the best they can be. A place where they can be themselves – feeling welcome, valued, and included. Where they can keep growing and look after their wellbeing. So, if you share our ambition, join us at this exciting moment in our journey to get Ahead Together.

  
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