Recently, I chatted with Prisha, a master’s student who is navigating the job market in data science & analytics.
We talked about technical skills, networking, long-term career planning, and why it’s important to stay adaptable as the field evolves. (Spoiler: things will always evolve. Today, it’s AI. In 10-20 years from now, something else will come along and disrupt things. Never stop learning.)
Some of the key takeaways from the conversation:
Breadth beats niche early on
Having a wide range of projects and tools (SQL, Python, ML, text mining) is actually realistic and valuable, since real data science roles rarely use just one skill. The ability to pick the right tool for the problem matters more than mastery of one tool.
Projects should tell a business story
Hiring managers want to see that you identified a real problem, found the right data, and can connect your findings to actionable business decisions. Not just that you used fancy advanced models or a laundry list of data platforms.
Standing out requires more than academics
If you’re entry level, you’re competing against a pool of candidates with the same coursework and projects. Getting involved in extracurriculars, especially if you can take on a leadership role, or even getting a customer service job can demonstrate the soft skills and problem-solving that most junior candidates lack.
Referrals matter, but only if you’re a strong candidate
Cold emails and LinkedIn outreach can work, but people won’t risk their reputation on a weak candidate. Be specific, succinct, and make sure you are not just aligned to the role, but a strong candidate.
LinkedIn content should attract decision-makers
Posting about how you are learning analytics & data science will attract attention from fellow entry-level candidates who can’t hire you. If you want to build a personal brand that attracts recruiters and hiring managers, share industry articles with your commentary, or get involved in event planning for professional communities. This will help you connect with established professionals.
Networking is a long game
Coffee chats should be approached as information-gathering, not transactions for job referrals. Follow up every few months with meaningful updates or questions. If you see a job opening at their company, follow up about it. I don’t recommend asking “let me know if there are any openings at your company” - don’t put the work on them. They also probably aren’t paying attention to their company’s job listings.
Stay adaptable as the industry shifts
When I was still working in marketing, social media and digital channels transformed the industry from 2006 onward. Now, I see AI doing the same thing to analytics & data science and a lot of other fields. If you are willing to continue to learn new tools and embrace change, your career will be better positioned in the long run.
