In Asia Pacific, BNP Paribas is one of the best-positioned international financial institutions with an uninterrupted presence since 1860. Currently with over 17,000 employees* and a presence in 13 markets, BNP Paribas provides corporates, institutional and private investors with product and service solutions tailored to their specific needs. It offers a wide range of financial services covering corporate & institutional banking, wealth management, asset management, insurance, as well as retail banking and consumer financing through strategic partnerships.
Worldwide, BNP Paribas has a presence in 73 markets with more than 196,000 employees. It has key positions in its three main activities: Domestic Markets and International Financial Services (whose retail-banking networks and financial services are covered by Retail Banking & Services) and Corporate & Institutional Banking, which serves two client franchises: corporate clients and institutional investors. Asia Pacific is a key strategic region for BNP Paribas and it continues to develop its franchise in the region.
BNP Paribas offers you an exciting career in an international business environment that is fast-paced, diverse and focuses on creating high-value relationships with our clients. We offer competitive salary and benefits, as well as a working environment where you're valued as part of the team.
* excluding partnerships
Role is part of the Business Analytics team of BNPP Wealth Management Asia that uses analytics and statistical methods to uncover insights from data, to inform and guide business decisions.
Candidate will participate in all kinds of analytics initiatives, ranging from exploratory data analysis, building predictive models to delivering analytics insight reports to business users. He/she would be someone who is curious to find out why things work or don't work, what are real drivers or causes of results, and what kind of levers or practical measures can be used to influence change .
1. Deliver data analytics projects
• Carry out analytics activities at all stages of the data analytics life-cycle - understanding business needs, sourcing, cleansing and transforming data, conducting exploratory data analysis, developing and validating models and explaining analytics results, implications and proposals in business terms
• Engage stakeholders to understand business issues & opportunities, and formulating it in a manner that can be analysed and modelled
• Plan and track progress of analytics development activities
• Identify and obtain data relevant for the analysis, ensuring that proper data cleansing, transformation and aggregation rules are applied, explained and documented
• Apply appropriate tools – R, Python, Tableau, Business Objects, SQL – for data extraction, discovery, aggregation, statistical analysis and visualisation
• Translate analytics findings and insights into actionable business proposals and activities
• Prepare and present analytics findings and recommendations
2. Support ad-hoc analytics requests and regular reporting generation
• Engage stakeholders to understand business requirements
• Identify data needed to answer business questions, consult data and process owners to assess whether data is available, and if it is suitable for the task
• Use appropriate analytics tools to extract, cleanse, filter, aggregate and present data, with a focus on meeting business needs and quick turnaround
• Build and generate requested reports and dashboards, ensuring that delivery meets agreed timelines, insights are explained and analysis recommendations are actionable
3. Department Support
• Support department initiatives and
• Collaborate within BA team in joint analytics development, problem solving and issues resolution
• Support BA software application / tools enhancement / upgrade activities
• Cover BA team members' duties in their absence where needed
Technical & Behavioral Competencies
• Critical thinking skills – ability to use data to find answers to questions, to uncover and synthesize data, behaviours and outcome connections
• Data Visualisation skills – understanding of the science behind visualisation choices, and expertise in designing effective, high quality charts & visuals to present findings in a clear, concise way
• Excellent communication and presentation skills – ability to understand business problems, summarise expectations, explain analytical results and recommendations clearly in business terms
• Problem solving skills – ability to assess situations, verify facts, formulate and propose alternatives.
• Interpersonal skills – ability to interact with ease, collaborate with diverse teams, establish rapport and build trust.
Specific Qualifications (if required)
• 1-2 years hands-on experience implementing data analytics projects, or at the minimum, hands-on experience in one or more phases of the analytics life cycle.
• Bachelors or Master's degree in Data Science, Data Analytics or Applied Statistics
• Expert level competency in one or more of the following tools - R, Python, Tableau, Power BI, Business Objects and SQL.
• Proficiency in Microsoft Office and SharePoint collaboration tools.