Site Name: Bengaluru Luxor North Tower
Posted Date: Sep 22 2023
Key responsibilities
Business and data understanding: Working with other data scientists, you know how to build your understanding of the business context, systems, environment, strategy and people aligned to the given area. This also includes an understanding of the relevant internal and external high-volume data sources, validity and domains of such data to align with the intended business objective. You will conduct data acquisition from multiple data sources and wrangle data sets selecting appropriate techniques, such as parsing, or an algorithm, to create a data structure relevant to the problem.
This can include but not limited to techniques such as ETL batch processing, streaming ingestion, scrapers, APIs and crawlers. NOTE: adjust here based on your teams process of identifying DS project scope. Could also be the case, for example, “After receiving an explorative brief, you will build your understanding of the business context, systems, environment, strategy and people to convert it into a valued deliverable.”
Data preparation: You will create required data set(s) utilizing your understanding of complex business problems, data formats, applicability of the data to the problem and standard modelling techniques. You can perform techniques to validate the quality of the data, and can fuse data from various sources using knowledge of data pre-processing techniques.
Modelling: For the intended business objective, you can utilize advanced modelling techniques, such as predictive modelling, advanced clustering, association rules, to create a model or models that perform to particular requirements and specifications.
You are able to anticipate how a model’s requirements or the available data, might change over time and be able to design a product that will be able to cope with these requirements.
Test & validate the model: You are able to apply best practice model fit testing, tuning and validation techniques, such as chi square, ROC curve, root mean square error, to assess model performance, compare results from various methodologies and suggest improvements. You both give and seek feedback and ideas with others from across differing business areas, as relevant, to create better products and continually advance your data science skills.
Communication of insights: You are able to design rich data visualisations and use them to communicate complex messages to business leaders in a clear and simple way,
with the ability to respond effectively to challenges.
Why Us?
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 organization where people can thrive. Getting ahead means preventing disease as well as treating it, and we aim to positively impact the health of 2.5 billion people by the end of 2030.
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 workplace where everyone can feel a sense of belonging and thrive as set out in our Equal and Inclusive Treatment of Employees policy. We’re committed to being more proactive at all levels so that our workforce reflects the communities we work and hire in, and our GSK leadership reflects our GSK workforce.
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