Fintech Talk - Part 2: "Genz and Career Prospects" - With Ms. Thao Nguyen - Product Owner (SSI)

Ms. Thao Nguyen currently holds the position of Product Owner at SSI Securities Joint Stock Company, with nearly 8 years of experience in the securities industry in general and Financial Technology (Fintech) in particular. Especially, she has completed a Master's course in Fintech at the University of Edinburgh, United Kingdom, under the Chevening scholarship program of the British government.

Through a profound understanding from the perspective of a pioneer with extensive experience in the field, Ms. Thao Nguyen will share valuable information and interesting career stories with students. The insights shared this time will help students better understand the opportunities and career prospects in the Fintech industry.

As shared in part 1, after graduating with a Master's degree in FinTech, Ms. Thao holds the position of Product Owner for the online trading system at SSI Securities Company.

1. Could you please provide a more detailed description of this job so that students can have a clearer understanding?

As introduced, the Product Owner (PO) position is responsible for the product aspect, accompanying and guiding Business Analysts (BA) and the software Development team to provide transaction solutions to serve business and create value for investors.

Firstly, we need to understand that BAs act as a bridge to transform business requirements into software requirements so that the Development team can program and implement various technical tasks. Imagine business and technical individuals speaking different languages. The role of a BA is to bridge these languages so that both sides can understand and work together towards a common goal of creating value for customers. Therefore, the BA position requires not only knowledge of business (such as securities, in my case) and IT system operation within the organization but also many skills related to coordinating business tasks to be developed on the system, managing stakeholders, leadership, communication, and negotiation skills.

The person holding the PO position plays a continuous guiding role for the BA and Development teams regarding the soul and vision of the product, building deployment plans, coordinating stakeholders to achieve plans, and making final decisions related to delivering the product to customers.

Since the outputs of the work of PO/BAs will be used as inputs for system development, the roles of PO/BAs are extremely important in any software project in any field. I assess the PO/BA positions as very interesting and comprehensive roles in both knowledge and skills, always demanding continuous self-improvement. It would be very worthwhile to try, dear students.

Through the Fintech course in the United Kingdom, I have also been exposed to trending technologies in this field such as Machine Learning and Blockchain, ready to apply these technologies for the breakthrough of stock trading systems in the future. I believe that this knowledge will be a valuable asset and open up many opportunities in the context of AI constantly developing and infiltrating into every aspect of life, not only in finance or investment.

2. In the FinTech industry, how does the typical career advancement path develop?

In reality, FinTech is very broad, covering many branches depending on the type of business and business model. However, it can be divided into 2 groups:

• Group 1 consists of software development companies (for example, in Vietnam, there are FPT Software, CMC, NashTech..., and globally there are Google or Microsoft).
• Group 2 includes businesses that operate their own products/services and require technology applications to provide those products/services. This group can be any business, from small and medium-sized enterprises to large financial conglomerates. They build their own system development teams and combine them with products provided by Group 1. With the current trend of data-driven business (making business decisions based on data analysis), any financial institution needs to leverage the vast data resources of the industry. Not only banks, securities companies, insurance companies, investment management corporations, and venture capital funds have also joined the game.

Therefore, the career advancement path in the FinTech industry also depends on the organizational model of each specific business. However, according to my understanding, the technology field requires continuous updating, and it is rare to "live long and become a veteran", so the career advancement path will depend entirely on individual capabilities. Regarding the positions in the industry and the career path of each position, I will follow the software development process for easier understanding.

Traditional software domain

1. Generating software requirements: Business Analysts (Junior/Senior) are responsible for this task. They are then promoted to become Product Owners, who are accountable for the product. Next is the Product Manager, who can manage and have a broader vision of a larger product ecosystem.

2. Development team: Typically consists of 2 positions: Developer (Junior/Senior). The hierarchical levels for this position depend on the organization and may include Team Leader or Manager. In terms of expertise, this position aims towards Solution Architect, who plays a role in directing the technical system on a broader scope.

3. Tester/Quality Assurance – responsible for software testing and quality management, including directing and building software development processes for the entire business. The hierarchical levels of this position are similar to Developers and may include Team Leader or Manager.

4. Other positions:

- DevOps: Involves deploying software through processing stages (deployment) onto systems such as databases or servers.

- System operation: For software to run and reach customers, there are various involved parties. This team ensures system performance factors and user support, with hierarchical levels similar to Developers or Testers.

- Project Manager or Scrum Master (for projects running on the Agile-Scrum flexible model): These positions focus on project management and support project operation processes as well as the spirit of software development methods. Those who prefer leadership, management, and resource coordination roles can explore these positions.

- Sales and customer care: These positions are often found in Group 1 software development companies. This team also needs knowledge of the software field and the industry they serve to successfully sell the product.

Consultancy Domain

- Students can explore consultancy services in system implementation provided by the Big4 consulting - audit firms (Deloitte, Ernst & Young, PwC, KPMG). If they read reports on the global Fintech industry, they will come across many reports from these Big4 firms. They can play various advisory roles in the implementation of software in general and the application of technology in financial companies in particular. For example, they may advise during the tendering phase (suppose company A needs to purchase software, and there are many software providers participating in the bidding. Consultants will advise company A on the suitability of these software partners, cost, operational model, product orientation, team, etc.). They can also advise on project software implementation, applied technologies, or which Fintech branches are suitable for the business.

- Consultant/Coach positions: These positions are often found in projects running on the Agile-Scrum flexible model, aiming to ensure that software projects run according to the model and ensure effectiveness. However, in Vietnam, the application of Agile still has many limitations in practice, so people with knowledge and experience in Agile are in high demand.

Data Science Domain: 

Generally, if the objects that the above-mentioned groups deal with are product-related issues or business operations, then for the data group, the system will perform database mining to find insights to support business decisions or operational decisions, or build algorithms to conduct automatic analysis and predictions. The applied technologies therefore vary. However, these two groups generally intersect to create a complete product. For example, a data mining algorithm to predict the outcome of stock trading strategies will also be integrated into a software system, through a user interface for customers to access and use. Of course, positions in the data science field also depend on the definition of each organization. There are some common positions in this industry such as Data Analyst, Data Engineer, or Data Scientist.

1. Data Analyst: Typically works with data analysis tools to uncover insights, often through visual reports and graphs, serving as input for leaders to make business or strategic decisions. For example, a Data Analyst might analyze data on stock brokerage over the past 10 years and create charts showing aspects indicating which brokerage department operates most efficiently. There are many criteria to evaluate "efficiency" in this case, so being a Data Analyst requires understanding of the industry as well as data analysis tools, methods, and presentation skills to uncover the "story" that the data tells.

2. Data Engineer: Focuses on processing data as input for more complex models or algorithms. These individuals require deep knowledge and skills in programming, responsible for collecting data sources, cleaning data, and organizing them to build a database that meets the requirements of algorithms or system processing. This position is not only found in specialized data science fields; even regular businesses with large databases may have this position. Imagine that business operations or features of a software product are like parts of the human body, each part has its own function and operation, but blood flows throughout the body. Data is similar; the processing flow of a system begins with how data will flow through the systems within the same ecosystem.

3. Data Scientist: This is currently the hottest position. They need to understand data, mathematics, probability statistics, and data processing algorithms such as Machine Learning or AI, for example. Data Scientists typically work with large datasets to build algorithms to test assumptions, make predictions, and automate future analyses based on available data. For instance, they may design about 10 stock trading strategies, run tests with 10 years of historical data, and build a model based on hundreds of related factors (parameters) to predict which strategy will succeed in the 2023 market context. In other words, Data Scientists build tools that can tell the story of the future through past data that the tool encounters (training). This job requires a complex set of skills, not only technically but also a deep understanding of the field they are involved in, to design comprehensive algorithms suitable for that field.

4. Regarding career advancement, these positions also have various managerial levels similar to the traditional software domain.

The Faculty of Finance would like to send huge thanks to Ms. Thao Nguyen for the informative and detailed discussion. We wishes her good health, happiness, and enthusiasm to contribute to the development of Financial Technology in Vietnam. 

Through this, Tachi hopes that students have found answers to their concerns about creating and following their career path. We hope to see you again at the next events organised by the Faculty of Finance, specializing in Financial Technology (49K33)!