Data Scientist

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**Key Skills (mandatory)**
- NLP, Timeseries, ML and Deep learning
- SQL
- Azure cloud services work ex
- Good python knowledge
- Debugging skills in Python
- Experience in Pytorch or Tensorflow
- Productionization of models
- Data visualization tools like PowerBI

**Detailed JD**:
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**Overall 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.
- ** 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.

**In the role, you will**

Work in a stimulating and supportive environment; Be part of a dynamic, growing community of data analysts and data scientists at GSK; Have career-long access to our GSK Data Academy - a dedicated, tailored learning programme that blends your on-the-job learning with targeted coaching, peer-to-peer mentoring, expert-led workshops and a network of learning providers; Work on high impact strategic priorities; deploy GSK's large, varied data-sets to tackle analytics challenges; Be at the forefront of GSK's data and analytics transformation

**Core and Technical Competencies, to be successful in this role, you should**:

- Be curious and passionate about creative thinking and data innovation, enjoy problem solving and have empathy for the problems you are challenged to solve.
- Be accountable for driving projects and improvement activities through value delivery for GSK leaders from across different business areas;
- Be able to compile, integrate and analyze data from multiple sources to answer business questions.
- Have the ability to conceptualize, formulate, prototype and implement algorithms to solve complex business problems.
- Demonstrate the ability to communicate complex data science concepts to a variety of stakeholders.
- Have the ability to plan and execute value measurement of data work, in order to demonstrate and improve results.
- Possess practical experience developing and implementing machine learning on large data sets.
- Have knowledge in mining large & complex data sets using R, Python, SQL etc. from a multitude of environments such as cloud, Hadoop clusters, NoSQL or Spark
- Understand statistical modelling techniques and the mathematical foundations of applied ML and AI algorithms and models.

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**Basic Qualifications**
- Total 8 to 14 yers of IT relevant experience from reputed IT company
- ~6-8+ years of experience of working in Data Science or related role.
- Hands on experience on any Cloud Platform - preferable Azure
- Working knowledge cloud based and local data science frameworks and toolkits.
- Working knowledge and experience of project management methodologies, include Agile methodologies and the hypothesis-driven approach
- Have a practical understanding of Machine Learning, Deep Learning and natural language understanding/processing or speech recognition (if applicable)
- Experience of building large scale machine learning systems (if applicable)
- Exposure to Cuda, pyTorch or TensorFlow. (fill in as applicable)
- Nice to have experience of working in Finance/ Procurement domain.

**Overall responsibilities**