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Finding the Right Data Science Mentor [Checklist]

Data Science is still a fairly new field, and it can be tough to trace a career path. It’s vaguely defined, so job-seekers have leeway to build their ideal career, but it's a hard road. Finding a good mentor to help navigate the uncertainty can make all the difference.

The right mentor will help you stay on track, make connections, and support you when making tough decisions. But where to find these magical beings? And how will you convince them that you’re worth their time? At Exponent, we believe mentorship could be the perfect catalyst to accelerate your career, and we’re here to help.

Preparing for a Mentor/Mentee Relationship

Before you begin approaching potential mentors, clarify what you want out of the relationship.

  • Reflect on what you want from your career. It’s okay not to have a detailed plan, but you need to be able to articulate what you want and why. Think through which problems interest you. Is it the business side of things? Or are you fascinated with machine learning? This exercise will help you narrow your search for the right mentor, and your thoughtfulness will make you a more attractive mentee.
  • Distill what you’re looking for in a mentor. Career goals aside, what do you want from this relationship? How often do you anticipate meeting? What sort of issues do you want to discuss? You won’t have all the answers right away and it’s best to let the relationship evolve organically - but clarifying your “best-case scenario” will help you stay on track while searching. You’re also making your future mentor’s life easier as they won’t have to guess how to interact with you.
  • Craft your portfolio. Make sure your work represents you well. Show off your foundational data science skills in programming, data analysis, storytelling, and visualization. If you haven’t created a few passion projects outside of your work experience, take a few weekends to build something that will pique the interest of a potential mentor (or hiring manager!) If you’re unsure about how to build a portfolio, we’ve got you covered.
  • Google any technical questions. Don’t ask potential mentors anything that can be answered with a quick google search. Mentors aren’t referrals; you’re not hoping to impress them quickly with a fancy algorithm and then disappear. You’re building a relationship. Be a compelling choice.
  • Manage your expectations. Don’t expect DJ Patil to agree to mentor you if you’re still an undergrad. Don’t think of this as limiting; you’re being judicious. You’ll have many mentors throughout your life (and you can have more than one at one time!) and your dilemmas will change as you grow. There’s no rush. Look for someone whose interests and experience reflect your current status and goals.

Finding the Right Fit

Once you can articulate your goals clearly, it’s time to start actively looking.

  • Don’t limit yourself to big names. Instead, look for someone whose career trajectory mirrors what you want. Are you a career data analyst transitioning into data science? Or are you a newly-minted PhD with a passion for stats? Your journey is unique but a good mentor will be able to guide you through difficult decisions - all the better if they’ve been there before.
  • Look for a few key qualities. These will become clearer once you start interacting with potential mentors, but you should start looking now. The best mentor for you might not be headlining conferences, but they should be:

   This is just the beginning. More on choosing the right mentor later.

  • Think outside the box. Think you’re the first person to message Andrew Ng on LinkedIn? Platforms like this are easy, so everyone uses them. Meet people in real life wherever possible. Local meetups or hackathons are great for this because you’ll get a chance to showcase your skills and you’ll make many new connections in a short time. Even if you don’t meet your dream mentor, it’s likely you’ll meet someone who can make introductions. Some alternative places to look include:
  • Use all available resources. You’ve got even more options if you’re open to trying out a mentorship platform. Here are a few good ones to try:
  1. Exponent: Exponent is staffed with experienced product managers, software engineers and data scientists from some of the most sought-after names in tech - all available to you through a Slack community and personalized one-on-one coaching sessions.
  2. Codementor: Founded in 2013 by a Y Combinator alumnus, Codementor can connect you with seasoned mentors who can help you problem-solve and learn more efficiently (and even debug your code!)
  3. AnitaB.org: This one’s for the ladies. AnitaB’s mission is to support women in tech in a variety of ways, including connecting mentors, mentees, and building peer networks.

Engaging with Potential Mentors

After narrowing your search to a few names, start reaching out.

  • Respect their time. This is rule number one. Make things as easy for them as possible, and be cognizant of what you can bring to the table in exchange for their time. Don’t sweat it if you’re early in your career - even if all you can offer is an interesting thought experiment, you’ll have held up your end of the bargain.
  • Start slow, gradually expand, and be specific. Starting slowly is beneficial to you both. You don’t want to bombard strangers with information, and getting to know one another slowly will likely lead to a more organic relationship. Begin by asking a question about his/her  latest LinkedIn post, or ask their thoughts on an interesting piece of data science news. Once you’ve got your foot in the door, build communication slowly and predictably. Once you’ve emailed back and forth a few times, you’ve started to establish trust. Demonstrate that you’ve taken the time to think through his or her responses, and offer honest and helpful perspective in return - the mentor-mentee relationship is a two-way street after all.
  • It’s a marathon, not a sprint. You’ve connected with someone stellar. After an email or two, you’re ready to pop the question. Instead, pause: Do you feel like you know this person or are you starstruck by their resume? Do you like them? Will you be comfortable sharing? Ask yourself these questions before moving further and be brutally honest. Even if the answer is “no”, you’ll have made a great professional connection.
  • Understand that you’re still responsible for the outcome. Your mentor can guide you, but you need to put in the work. When facing a dilemma, think through the problem and come up with possible solutions before bringing anything to your mentor. When your mentor tells you something you don’t want to hear (and the best ones will), give it due consideration and take action. Your career should enrich your life and catalyze your self-improvement, and there’s no outsourcing. Taking ownership is scary, but exciting - and you’ve got someone in your corner when you need it.

Finding the right mentor will take time, but good things always do. In the meantime, keep moving forward. Contribute to an open-source project, compete in Kaggle competitions, or attend a hackathon. A strong and diverse network of peers can offer you support in the same way an experienced mentor can. And if you’re ready to take the next steps forward in your data science career, check out Exponent’s career prep offerings.

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