Find a Mentor 

In my eyes having a mentor is one of the most important things you can do to aid you in becoming a successful data scientist. I was fortunate enough to find someone willing and able to invest time in teaching me when I started as a junior data scientist, for which I am forever grateful. Before starting to find a mentor, make sure you’re ‘mentor-able’, this means having the right attitude to be mentored, which hugely consists of staying humble and appreciative for their time. This person will provide you with wisdom and teach you to think in a specific way. After all, they themselves spent hundreds of hours figuring out and/or receiving mentorship themselves. Whilst the thought of approaching an expert and asking for help may seem intimidating, you’ll be surprised by just how many may be willing to help. After all, their career may have given them so much, they may feel a responsibility to pay it forward. If they like you, they’ll gain satisfaction in watching you progress and happily trek with you through the dense jungle of data science. 

So how do you go about finding a mentor? Here are the main 4 ways:

  • Assigned a mentor through work 
  • Pay for tutoring / training 
  • Someone you know 
  • Reachout to people 

Assigned a mentor through work

All of these have their benefits and caveats. Mentoring through work is likely to be the optimal choice as you can get paid whilst being mentored, however, not everyone will be fortunate enough to have this as an option. If you do, it may be through one of two ways, you work for a company that has an in house data science team and supports mentorship for career transition. You may spend time working on a project with a data scientist, which you can use as an opportunity to ask questions and express your interests in learning more. Data scientists are often found in cross functional teams or ‘squads’. The other option is to join an apprenticeship or junior role where you are able to learn on the job quickly, this is likely to be the most efficient way to learn however you may have to accept a lower salary, or if in the case of an unpaid internship, nothing at all.

Someone you know 

Reaching out to someone you know in your social network is the next best option in my opinion. Think of people who know you well that have a close mutual friend. There’s no harm in asking, it’s unlikely someone in your social circle will be rude or very dismissive. In a way asking for their expertise can be a great compliment. If you don’t know too many people in the professional space, say you’re a graduate student, ask your parents, uncle, friends parents. Thanks to the six degrees of separation in social networks, the idea that everyone is mutually connected to everyone on average by 6 mutual connections, you only have to keep digging until you find the perfect person to help you.

Pay for tutoring / training 

There are plenty of data science bootcamps and training programs available online and offline where you can be assigned a mentor. As is the case with academics with real world experience, most masters programs will assign you a supervisor, however this supervisor will likely work with many students who will be short on time and may not have the full industry level experience that you seek.

There are websites that offer private tutoring online, however be prepared to spend a lot of money for the many hours of supervision you might need. Most people don’t have pockets so deep, so seeking cost effective or free mentorship is their only option. In my experience, the best mentors won’t ask for money as they are not financially motivated to help or have reached levels where any money they could earn through mentorship is somewhat unecessary. 

Reach out to people 

If you don’t have any friends or acquaintances in data science, then reach out to data scientists via email, Linkedin, Twitter or any other social platform. It could be something as quick as a comment on something they posted, data science blogs are a good place to start. Have a clear idea of the sort of person you want to learn from, someone who is in the position or industry you envision yourself working in a few years from now. If it’s data science for finance you’re interested in, reach out to data scientists working at fin-techs or banks.  Good data scientists receive multiple cold messages a week from recruiters; they may find it refreshing to receive your message. If the person has published some work, contributed to an open source project or has written a blog post, read it and mention it. The trick is to find a way to build an authentic relationship, for example don’t suck up and praise work you haven’t read. Be honest and open about what you hope to gain and mention what they could learn from the relationship (mentors often find the process mutually beneficial for their own development) and don’t get disheartened if too many people say no.

Once you find that mentor, work on building a positive relationship with them as best you can. It could be one of the most important relationships you have in terms of their impact on your career. Once you have a clear and efficient dialogue set up you can begin unearthing their wisdom. A scarce and valuable resource.