Data Science Role - KPO

Purpose statements:

- Partner with Data Scientists, Sales and Marketing teams on the formulation of customer solutions

- Build innovative analytical solutions and meet with prospective customers to assess their needs and develop the best configurable solution for a business need

- Work closely with business stakeholders to assess their needs, scope detailed requirements, advise on business rules and testing strategies and co-create innovative data solutions to business problems

- Research analytical options, designing features, prototyping and testing algorithms to create solutions to identify and drive improvements

- Identify business issues and use data science based techniques to drive tangible and actionable change benefitting customers and the business

Experience statements:

- Experience in delivering projects with cross-functional teams and the ability to work with Data Scientists and Engineers

- A proven background in delivering Data Science/Big Data projects for stakeholders

- Knowledge and experience of data mining, machine learning techniques quantitative and qualitative research and analytic methods.

- In Depth understanding and application of statistical models and machine learning techniques such as Random forest, Logistic Regression, Na- ve Bayes, Boosting Techniques etc.

Personal attribute/skills:

- Curious to solve business problems with correct application of data science algorithms

- Strong communication and presentation skills

- Ability of articulate complex business problem statement into an analytical problem

- Enjoys learning new things, comfortable working in unstructured, demanding and dynamic environments

- Highly collaborative and inspiring, strong influencing skills and an ability to work across organisation /channel boundaries

- Strong data driven/analytics/measurement focus

- Passionate and resilient agile, goal orientated and delivery focussed.

- Able to make sound judgement and priority calls

- Commercial, strategic and risk awareness, able to make sound judgement and priority calls

Qualifications:

- A degree in a quantitative discipline Engineering or Statistics

Technical level:

- Hands-on experience in SQL and R/ Python etc.

- Experience with ETL tools like SSIS, Alteryx

- In-depth knowledge of Predictive Modelling, Statistical Modelling ,Machine Learning Techniques

- Experience on visualisation tools like Spotfire, D3.js. is a plus