Senior Data Scientist, Analytics

Key Skills

Algorithms, Big Data Technology, Data Analysis, Data Mining, Data Modeling, Data Visualization, Java Programming, Machine learning techniques, Management, PowerBI, Python Programming, R Programming, SQL

Job Description

The customer is the focus of everything we do, and millions of end users rely on our products daily. We believe in the value of empowering Senior Data Scientist, Advanced Analytics with the resources to solve critical problems for the future of our business, which is why we need you.

Key Focus: Reporting to the Head of Advanced Analytics, WAM Asia, the Senior Data Scientist will take a leading part in the management of the advanced analytics programme to enable Wealth and Asset Management Asia in developing world class, robust, revenue generating, data analytics driven marketing strategies and customer value management program.

What motivates you?

• You obsess about customers, listen, engage and act for their benefit
• You think big, with curiosity to discover ways to use your agile mindset and enable business outcomes
• You thrive in teams, and enjoy getting things done together 
• You take ownership and build solutions, focusing on what matters
• You do what is right, work with integrity and speak up 
• You share your humanity, helping us build a diverse and inclusive work environment for everyone

We are looking for someone with:

• Master’s Degree or an advanced degree in a quantitative discipline (Business Statistics, Applied Mathematics, Computer Science, etc.).
• 8 years+ experience developing of probabilistic models, data mining, and machine learning algorithms, including real world experience of applying analytics models and techniques in the marketing and customer value management area. Candidates with less experience would be considered for the Data Scientist position.
• Expert in data analysis using Python, R, SQL and data visualization package such as PowerBI and Tableau
• Hands-on experience in deploying analytics embedded campaigns including targeting, test and control development, response tracking and analysis. Experience in Web Analytics such as Adobe a plus
• Hands-on experience of multivariate analysis, modeling, segmentation, and customer analytics using statistical techniques
• Strong business domain knowledge gained from the insurance, banking, investment management and/or consultancy industry.
• Strong communication and presentation skills. Ability to prepare presentation slides and present data reports/ analyses and statistics in a simple and clear way.
• A team player with the ability to successfully manage interaction with internal clients and work independently and within a team environment with professionalism and collaboration
• Experience working in the regional team and/or consultancy would be an advantage? 

On the job you will:

• Lead Data Science and Analytics projects with high impact on sales growth, business profitability, client retention and customer satisfaction.
• Lead complex data mining and customer analytics projects from creation, evaluation, testing and continuously improving using machine learning, and other analytics techniques.
• Innovate & find creative ways to drive the customer value creation and improve the effectiveness of marketing programs through leveraging internal data & external data, structured & unstructured data, and big data technologies.
• Strong ability to generate relevant, actionable insights based on iterative data analysis, translate data-driven output into business language, and to make appropriate recommendations to respective business stakeholders
• Provide expertise on analytics concepts for the broader advanced analytics group, and inspire the adoption of advanced analytics, data engineering and data science across the organization

Our commitment to you

• Our mission; to be a part of making Decisions Easier and Lives Better 
• A leadership team dedicated to your growth and success
• A bold ambition and set of goals to be a leader in driving transformation in our industry
• Our best. Every day.