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MISC
By 29 June 2016 | Categories: Misc

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Today, companies are collecting an ever-increasing amount of information from different channels and sources. With growing competition in financial services, companies need to use data to understand their customers better and engage more intelligently to retain their customers.

With digitisation constantly changing the channels with which consumers interact with companies, using big data to create personalised and authentic experiences will become even more critical for banks to retain intimate relationships with their customers. For example, Absa launched predictive alerts to customers who were unable to meet regular payments, offering them a personalised option to help them better manage their finances.

Helping to unleash this gold mine of value, hidden in company data, are data ‘wunderkinds’ (Data Product Managers) and Data Scientists. Thanks to their specialist skillsets, these wunderkinds help convert big data into actionable insights and create ‘wow’ experiences for customers as well as top-line business value.

So what do Data Product Managers do?

These rare individuals combine expertise and skills across six fronts: big data and analytics; commercial acumen; agile execution; design; digital; and customer experience. Working across the product lifecycle, they help to translate the output of a data scientist into authentic intelligent experiences for the customer.

In concert with designers and the operations and marketing teams they help to bring the back-office efforts across modelling, engineering, and development to the forefront – helping to make sure the work of data scientists see the light of day.

What does a Data Scientist do?

Data Scientists, are the backbone of value and insights created from big data. Mining raw data, they use programming skills combined with mathematical modelling techniques and out-of-the-box thinking to create engaging data products. They make use of resources available in open source communities to create an optimum enterprise solution.

Top 3 Skills to be a Data Product Manager

1. At Absa, data product managers must have a strong background in design, digital and customer experience, which help to create optimal end-to-end experiences.

2. No set educational path is necessary but a willingness to learn, and a passion for precision and creative thinking is ideal. Yasaman Hadjibasji, Chief Data Officer at Barclays Africa, worked in different teams including being responsible for Innovation and Customer experience in O&T.

3. Flexibility. Data Product Managers work in concert with a huge variety of teams and need to be able to manage these effectively.

Top 3 Skills to be a Data Scientist

1. Data Scientists don’t have to come from a background of computer science, although a strong numerical background is preferred. People can learn to code. At Absa, Data Scientists work with a variety of programming languages such as R, Python, Spark and SAS.

2. Strong problem solving abilities and enthusiasm to get deep into the data to unleash insights.

3. Strong communication skills. Story-telling has become an essential skill in data, in order to translate your technical findings to business stakeholders.

In conclusion, it is Data Product Managers and Data Scientists who will help to catalyse the value of big data in financial services sitting within company’s data, driving efficiency across the business and creating exciting and personalised experiences for customers.

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