Lawyers tend to specialize in certain areas of laws: finance, corporate, shipping, insurance and so on. My own observation is that most lawyers receive an all-rounded legal training before they (by choice, by chance or by a mix of factors) focus on a particular area and become a specialist lawyer. The specialization is a continuous process rather than an abrupt switch, whereby the lawyer with his legal training gradually learns about the industry that he is specializing into over the years. For example, a junior lawyer may not know much about finance from day one, but if he wishes to practise as a finance lawyer he must gain a deep understanding on the functioning of the financial markets and instruments. This process often takes years, as the lawyer needs to learn about a discipline that is not his original one.

There are exceptions to this career trajectory, of course. Some lawyers had been trained in other professions before they retrained themselves as lawyers. Sometimes those previous backgrounds have a bearing on the lawyer’s choice of specialization. For example, a medical doctor-turned-lawyer has a natural advantage in practicing in medical law, an accountant-turned-lawyer may have a unique edge as a corporate finance lawyer.

I’m a mix. My legal specialization is finance, so I also started off as a lawyer who learned the ropes of finance bit by bit. But data science to me is the opposite: I did not practise or train myself into a data science lawyer: instead, I parachuted myself into learning data science (although, as I plan to explain in the future, I can draw some connecting lines between legal skills and programming skills). I completed a master’s degree in data science, where I learned about mathematics, coding, computer science, and many interesting subjects.

I now hope to come back to bridge the gap to law, starting from the data science’s side. I have a good premonition about this journey. Often times, lawyers are terrified at STEM subjects (who chose law because “I’m not good with numbers”?) but since I’ve been there, I think maybe (just maybe) there is a way to explain the STEM concepts to lawyers in a way that lawyers can understand.

Another reason for my attempt is because I hope to find intersections between law and data science or simply “law and data”. An obvious example of that would be “data privacy laws”. Therefore, I hope to write a series of articles on issues and concepts that appear in data privacy laws. Now compliance with data privacy laws can often be highly technical (in both senses of the word: both requiring specialised skills and requiring computer-related skills). Therefore, I hope my articles would also present a somewhat balanced perspectives between law and tech. Although my approach may start off more from the perspective of popularising STEM concepts for lawyers, hopefully these articles may open the legal and compliance perspectives to data scientists, engineers and the like.