About the job Associate Director, Data Science
Roles and Responsibilities
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Develop AI and machine learning
solutions to optimise business performance across different areas of the
organisation
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Use data analytics to help
in-country Marketing, Distribution and Operation teams to increase revenue,
lower costs and improve operational efficiency
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Identify actionable insights from
analytics solutions, and communicate this to relevant stakeholders to improve
decision making and drive business performance
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Develop in depth understanding of
the business and be able to advise the business on the right analytics approach
by participating in business discussions and presentations as applicable
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Explore alternative sources of
information, such as social media, blogs, mobile, and other digital data to
understand customer and distributor behavior and uncover business opportunities
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Work closely with business units
to govern the effective implementation of analytics solutions
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Develop processes and tools to
monitor model performance, as well as implement improvements as needed
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Implement analytical models into
production by collaborating with relevant stakeholders
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Provide training to analytics
resources in the countries on AI and machine learning methodologies, and
sharing of best practices
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Drive analytics innovation by
keeping abreast of industry’s trends, evaluating and adapting new and improved
data science approaches for the business
Quantitative metrics
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Number of use cases designed and
related conversion rates from Digital P&C customers to drive growth through
online to offline (O2O) sales
Qualitative benefits
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Enrich customer data including
behavioral patterns to nurture leads (to be further defined and measured)
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Implementation of new ways of
working/agile, resulting in speed-to-market and ability to execute with nimble,
empowered teams
Minimum Job Requirements
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Bachelor’s Degree in a numerate
discipline e.g. Data Science, Actuarial Science, Mathematics, Statistics,
Engineering, or Computer Science with a strong computer programming component
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At least 10 years working
experience, with extensive hands-on experience in developing AI and Machine
Learning solutions
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Proven hands-on experience in the
use of at least one advanced data analysis platform (e.g. Python, R, SAS)
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Exposure to all stages of data
analytics project lifecycle (scope definition, data requirements, extraction,
exploration, transformation, solution development, tracking)
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Demonstrable understanding of
data quality risks and ability to carry out necessary exploratory data analysis
and quality checks to validate results obtained
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Knowledge of a variety of machine
learning techniques (clustering, decision tree, random forest, artificial
neural networks, etc.)
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Tenacious, with a desire to ‘get
to the bottom’ of things with sound logical reasoning and deep analytical
ability
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Excellent relationship
management, strong team building, and the ability to work across business units
and functions to drive positive business outcomes
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Sound knowledge of programming in
SQL or other programming experience
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Articulate, with excellent oral
and written communication skills. Adaptable, able to interact and build strong
relationships with people from a diverse range of backgrounds
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Fast learner with a willing
attitude. Intellectually rigorous, with strong analytical skills and a passion
for data
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Experience in big data
environment and tools such as Hadoop, Hive, Datameer is desirable
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Fluency in both spoken and
written English. Any Asian language is preferred
Reporting Structure and Supervisory / Managerial Responsibilities