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We understand that no two organisations are the same. Find out more about how we've customised our talent solutions to help clients across South East Asia meet their needs.

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Career Tips: Data Science and Analytics in Financial Services

Watch the webinar

Data analytics and data science have been on the forefront with their increasing importance in the financial services industry for the past few years. As we transition further towards Industry 4.0, we can only expect these areas to grow alongside an increasing demand for data professionals. How can an aspiring data professional meet the current market’s expectation? What challenges might they face in their career path? How can they position themselves to land the best opportunity for themselves?

 

Join Robert Walters Malaysia for a panel discussion between two professionals in data analytics and data science. They will share their experience and valuable insights about:

  • Common mistakes made by data professionals during interview sessions
  • How data professionals can transition between financial services and non-financial services industries
  • Challenges faced in the data scene, specifically in financial services industry

 

If you wish to excel within data field, be sure not to miss this webinar as the panel speakers will also provide insights and tips to help you thrive in the world of data.

Speakers

Shaminee Muniandy

Shaminee Muniandy

Head of Analytics, Decision Science & CRM - Maybank

Possess almost 15 years of experience working with customer data from multiple industry. Close to 10 year of experience in Telco business starting as Pricing Specialist and venturing into Data Analytics and then took up the role of Data Scientist. Towards the later stage of working years with Celcom, she took up the role of Head of Customer Experience and Digital Analytics. Managing a team of 11 data scientist, focusing in driving business value using advance machine learning models.

As a Data Analyst and Data Scientist, she covered multiple areas of applying data into decision making. Building machine learning models such as Churn Prediction for Prepaid & Postpaid, predicting dormant customers. With more advance tools, she tutored the team to explore and build Customer Lifetime Value (CLTV) model, segmentation using internet browsing data also working closely with vendors on SCV and SHV models.

Maggie Lim

Maggie Lim

Principal Data Scientist - Celcom

Maggie currently works as a Principal Data Scientist managing a team of 10 comprised of data scientist and citizen data scientist in a telecommunication company. She builds a strategic, in-house data science capability and lead the delivery of advanced analytics solutions to address business problems and opportunity.

Prior to telco industry, she has 7 years of experience working in financial industry, specializing in product and segment analytics where she has transformed the business from a segment centric to a customer centric business via the development and implementation of a customer profitability model. She also has 5 years of experience in finance analytics, content analytics and has developed a persona-inspired segmentation for digital marketing in media and e-commerce industry.

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