Key Responsibilities

• Understand the usage of different statistical modeling methods, their biases, how and when to apply them, decide which method/s to use for a particular analysis and data set.

• Build experience in predictive modeling techniques, such as regression, classification, and clustering to create models depending on requirements and specifications.

• Build capabilities and expertise in Natural Language Processing (NLP) to be Global Quality Assurance organization’s voice in leading use-cases in the areas of text summarizations, sentiment analysis, topic modeling, trend analysis etc.

• Interact with business stakeholders to understand their business problem(s) and translate them into machine learning use-cases that are feasible and scalable.

• Build experience delivering innovative data science tools and solutions to stakeholders e.g., Shiny web apps, R packages, Power BI dashboards.

• Work with Tech partners to understand off-the-shelf ML offerings from Cloud providers, and customize them, as needed, to fit business needs.

• Design quality data experiments to drive personalized solutions for GxPs across GQA and R&D

• Automate quality data models and simplify quality data information management.

• Deliver solutions using Power BI and Shiny Web Apps with back-end platforms supported by Python, R and Apache Spark.

Basic Qualifications

• Bachelor's degree, preferably in a STEM discipline.

• Minimum of 5 years in advanced analytics/data science roles, with ample experience in Natural Language Processing (NLP).

• Top-notch expertise in either R or Python (preferred).

• Excellent ‘analytics’ mindset that enables understanding and translation of business problems into advanced analytics use-case.

Preferred Qualifications

• Advanced degree (MS/PhD) in STEM subject (e.g., Computer Science, Machine Learning, Artificial Intelligence, Statistics, Bioinformatics, Engineering, Mathematics, Chemistry).

• Experience communicating advanced data science concepts to business stakeholders and leaders in a clear and simple way, with the ability to respond effectively to challenge.

• Experience in Python-based design/coding. and local data science frameworks and toolkits.

• Practical experience building and implementing large-scale machine learning systems, using SQL, Hadoop, NoSQL or Spark to mine large datasets.

• Experience with the Microsoft Azure technical stack, Databricks, and GitHub.

• Experience in Agile methodologies and the hypothesis-driven approach.

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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