Our partner and Haverford alum Panos Panidis at AESOP Academy hosted a career coffee chat with his fellow Haverford alum Alec Hubel. Alec is Senior Data Science Manager at CoinBase and has prior experience at Facebook, Instagram and Twitter.
Key takeaways from Kristie Beucler, Associate Dir of Career Services at Swarthmore:
Technical skills to know are Excel, SQL and Tableau. Tableau is expensive, so it’s mostly used in organizations with a high budget. Soft skills are equally important. The goal for analyzing data is to utilize it to make decisions, thus communicating about the data and presenting it, likely to high level people in the organization, is a critical part of the job.
Alec gave some great interview advice, as well. He said be authentic and conversational. And when you are doing the technical part of the interview, talk through what’s going on in your mind. He said that you may not recall a precise code at the time, so tell the interviewer why you would do a certain thing, the goal you’re going for, etc. Talk through your intention – it’s OK to acknowledge that you don’t know the exact code. Also show that you can work autonomously and that you will be proactive in your work. He says that great entry level employees think of what the next step is or next question the manager will ask, and have goen to that level before the manager asks it!
Additional advice Alec gave was about networking. When writing an outreach email, attach a photo of a sample of your work. And, create a project with a data set and post it on the Internet. Pretend you are working at an organization. He noted that Kaggle is a free online learning resource for learning data analytics.
Additional key takeaways as noted by Panos, who moderated the talk, are:
- Data scientists conduct analysis, generate insights, assess trends, perform research, build forecasting and predictability models – all of which influence the strategic decisions & direction of the company. Company projects, products and forward-thinking strategies all come out of the data-backed findings from data scientists
- To develop data science / analytics skills, ‘learn by doing’ is the recommended way: apply skills on the job, utilize techniques in your coursework, or create your own self-starter ‘sandbox’ projects to explore methods
- Specific software to know: SQL, Tableau, Excel, Statistics tools (SAS, R, fundamental regression techniques), Python
- Growth areas: soft skills are as important as technical skills. Soft skills such as teamwork/collaboration, learning to present work and being able to articulate challenges and findings with team or leaders
- 3 BIG CAREER TIPS: (1) Be consistent & reliable – exhibit that you can drive tasks to closure and are accountable, even exhibiting reliability as a student to visiting professionals in career office events leaves a good impression (2) Show your work – walk the interviewer through your thought process and share work along the way to make it an engaging interview, share non-sensitive/non-confidential sample work with hiring managers in outreach emails as a simple picture of sample work can demonstrate proficiency (3) Connect with people – learn from others, build relations and partnerships with experienced professionals on and outside the job
- What leaders wish to see more from junior talent? Proactivity to get engaged and tackle work, more autonomy and becoming self-sufficient, anticipating business needs or next steps to move project along
