Utilising Data Science in Finance
An interview with Applied Data Scientist Bootcamp graduate, Damien Yahi, on his experience with Cambridge Spark and how he learned new skills to help him be more efficient in his job, whilst enhancing his future prospects.
What were you doing before you enrolled in the Bootcamp?
I was a business auditor covering capital markets in an investment bank. My work was to review business processes, risks and control framework and then propose recommendations to improve the setup. My audits could be front-to-back desk reviews, thematical audits, and fraud investigations. Excel was the tool I was using to analyze data.
Not knowing what could have been achieved by using more advanced analytics rather than Excel limited my ability to have new ideas and deliver more impactful audits."
What challenges or friction did you encounter with your existing skillset?
Capital markets are a very technical area with many financial products and a complex IT infrastructure. In addition, the business has been investing significantly in new technologies (e.g. big data, blockchain, machine learning, bots...). Things are changing quickly and expectations around data and technology for each employee are increasing, for instance, all the big investment banks are now training their graduates to code no matter the role and coding training program is being rolled out in different areas of the business.
As an auditor, you have to be able to understand data and technology well to be able to properly challenge the business and manipulate the data by myself.
Why did you choose Cambridge Spark as your learning provider?
Ultimately everything is available on the internet regarding Data Science. However, it is scattered all over the place, therefore, it is really difficult to know what to learn and how to learn if you don't have the right support and tools. In addition, this field is evolving all the time.
While you can learn bits and pieces here and there, it is important to have a clear training path. Knowledge is like a tree and it is important to understand the key principles before getting into the details, therefore, having a good training path is the key to success.
Data Science master degrees at university are relatively new and very expensive and would in most cases require a full-time study, therefore, they were not an option. There are many online courses but most of them focus on a particular aspect of data science and do not provide this holistic training path we were looking for. The Bootcamp solution appeared to be a good solution as it provides a 360° view of data science while being very practical. The preference was to have continuous learning rather than a full-time Bootcamp in a short period of time.
Based on LinkedIn profiles of the teachers but also the students, we chose Cambridge spark. To be noted, the quality of the Cambridge Spark Bootcamp has been recently recognised by the government which provided recently a significant grant to further develop their educational tool, K.A.T.E ®.
It is difficult to do evening courses after work, therefore, courses during the weekends appeared to be a good option."
What did you enjoy most about the Bootcamp?
Learning new things was the best thing for sure. When you start working and finish your studies, you continue to learn things but in a different way. Being back at school gave me a huge amount of knowledge in a relatively short period of time! The teachers were knowledgable and the courses were quite hands-on therefore you could see immediately how to apply the concepts at work.
The other good thing is the good atmosphere with the students and the Cambridge team. Students have very different backgrounds so it is quite interesting to discuss and discover different areas. It also shows that data science is applicable anywhere no matter your company and your position. There was also a good social life during the Bootcamp (drinks after the course, dinner in some of the Cambridge Colleges...).
Each weekend opened the doors to interesting areas that were all new to me. This bootcamp truly changed my way of looking at data and technology, at work but also in my personal life."
How would you sum up your overall experience of Cambridge Spark?
Each weekend opened the doors to very interesting areas that were all new to me. This bootcamp truly changed my way of looking at data and technology, at work but also in my personal life. This Bootcamp was quite intense (be ready to work hard!) but it was really a great experience.
What advice would you give for those considering the Bootcamp?
I did not have any coding experience prior to Cambridge Spark. People without coding experience may be intimidated by the coding and the table of contents of the boot camp. Don't be afraid of coding and machine learning.
If you are curious, perseverant and good at problem-solving then you have all the qualities to succeed in this data-camp.
For people without a computer science background, I would strongly advise starting to study at least 3 months in advance the basics of Python, some mathematics and some high level reading about machine learning to help to have some background and be ready for day one (Cambridge Spark will provide you with some material and exercises to help you to prepare). During the certification, you have to be ready to work between courses as you will have to submit codes on a regular basis and learn a lot of new concepts. It is a challenging but very rewarding experience.
The impact was immediate as my role to a new auditor role focusing on data analytics and E-trading. These new skills helped me better understand the business through the lens of data and technology."
What are you doing now?
Cambridge spark provided me with great knowledge and a good overview of data science. The impact was immediate as my role in a new auditor role focusing on data analytics and E-trading.
These new skills helped me better understand the business through the lens of data and technology while delivering new types of audit tests and tools using these coding skills and my business understanding.
It is interesting as it is an emerging field in the audit functions, therefore, a lot of new initiatives happening. Audits functions are currently moving into more data & technology-driven departments but a lot of things still have to be built.
What does the future hold for your career?
There is a growing need in the audit industry to have data analytics skills in addition to business knowledge and audit techniques but it is still rare and difficult to combine all these skills.
Overall there is a high demand in the Financial Services industry for people having a mix of business knowledge and coding skills. Having done this certification will be, for sure, a strong asset for my career. In addition, this certification gave me all the foundations so I can continue to learn by myself to continue to improve my skills.
Could you sum up your perspective on the data science field?
Data science is a very interesting field because it is a relatively new field (some theories have been there for decades but actual implementation started relatively recently) therefore the profiles are quite diverse and not standardised yet.
The job title 'data scientist' can mean very different things according to the company and the team, therefore, both companies and candidates need to be careful about what are their expectations.
In the financial services industry, having coding skills are going to become mandatory everywhere no matter your position, therefore, it is important to build these foundations right now and be data-savvy.
The need for a data scientist is going to continue to grow for sure therefore there will be more and more opportunities. It's worth noting that you don't need to have a 'data scientist' title to be able to use the skills you are going to learn during the data Bootcamp: there is a high chance that you could start to use some of the skills in your current position and demonstrate you can bring value to your team with these new techniques.
Data is going to be ubiquitous, embrace the revolution!"
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