Check these out:

• Digital Analytics Association
• International Institute for Analytics
• INFORMS (focuses on operational research and analytics)
• Data Science Association
• Predictive Analytics Worldwide

Salary:

Salary ranges for Entry-level jobs can range broadly, from mid 40's to nearly 100k depending on the company, position, and your qualifications. Established tech companies, for instance, tend to pay really well and often offer stock packages that include generous benefits and vesting privileges. Startups, on the other hand, generally pay less, but offer candidates other perks, like company equity to incentivize performance.

Alumni advice:

Major(s)/Minor(s):

Political Economy

Title:

Engineering Manager, Data Science

Location:

Bay Area

Field:

Data Science

What is it that you do? What are the duties and responsibilities of your particular job? What is a typical and atypical day/week?

I lead and manage the analytics team in the data science org at GitHub. I am responsible for the data strategy of the company, which involves both how we evaluate our performance and how we can use data in our products to make them better for customers. I am in meetings 80% of the week about company strategy, product development, 1:1 management, project management, and recruiting/hiring. The rest of my time involves some coding and a lot of catching up on email.

What type of entry-level positions are typical for this field? What does your organization look for in an entry-level candidate?

Entry-level positions are difficult at startups because they often lack robust training structures. Bigger companies offer a lot more options. We tend to look for a quantitative background before hiring. The best candidates are thoughtful about how humans use technology and can walk through how we can link product strategy to the user experience to behavioral data.

How do people find entry-level work in this field?

Networking and having a data portfolio/blog are the best two ways. If you haven't worked already, we want to see proof that you are a thoughtful and skilled data analyst who can learn new technologies before bringing you on. It can be hard to break into the industry, but once you do the demand for jobs is both large and (so far in my career, until the next bubble burst…) constant.

How can students best prepare themselves in college to work in your field? (e.g.campus activities, courses, internships)

2-3 statistics courses and 1+ CS course go a long way, but applied knowledge of those concepts either in class or in internship is much better. I like to see either quantitative or technology-related internships or coursework. If you're in a technology internship that isn't data-related, try seeing how you can use the company's data systems to improve your team's workflows. If you're doing research with a professor, get good at R or SPSS or SQL or python or some combination of the above. Reading tech news and developing opinions about products is helpful. Participating in Kaggle competitions can be good experience, too.

How has your liberal arts education helped you/not helped you in your position?

Seeing how the many different puzzle pieces fit together has been immensely helpful in my career. I once wasn't allowed to advance at Google because I hadn't majored in computer science; I studied Political Economy. It felt like a huge barrier at the time, but I am now very glad I took a wide range of classes in both technical and non-technical fields, and I do not believe my non-CS degree has held me back at all. Studying art history gave me a solid foundation for how to think about design, and taking a religion class really helped me how to think about managing groups of complicated people. The Valley is getting much more open to diverse backgrounds, which is a great thing in my book.

Is professional preparation/graduate school or licensure/certification necessary for your position? Immediately after college, or after some experience? What kind of entry-level position would you recommend for someone to get started in this field before attending graduate school?

Data Science grad programs are emerging, but they are not necessary yet! For my field, go to grad school if you want to; you don't need to. It can be helpful for machine learning and AI positions.

What was your first position, and what other positions have you held before your current one?

My first position was a research associate at NERA Economic Consulting. I've held data analyst jobs at Google, Beats Music, and Apple before managing a team first at TuneIn and now at GitHub.

While Business Analytics and Data Science internships were rare a decade ago, there are increasing number of internship opportunities in different industries and company types, including marketing, consulting, finance, consumer products, startups, and, of course, all kinds of technology companies.

While Internships in Business Analytics or Data Science are required prerequisites for either field, they help make students more competitive for entry-level jobs in the field. To be competitive for either internships or entry-level opportunities, students should have demonstrated quantitative skills and coursework (or, ideally a quant major). Broadly speaking - the types of skill sets, coursework, and experiences that make a student competitive for consulting also make them competitive for opportunities in Business Analytics.

Job Search Links

• LinkedIn Jobs - One of the best resources for Business Analytics and Data Science internships and connections.
• Glassdoor - Surprising depth and breadth of Business Analytics and Data Science Internships and opportunities.
• Indeed - General career search website with array of different Business Analytic related opportunities.
• Simply Hired - Similar website to Indeed.com; decent opportunities in both Analytics and Data Science.

Resources

• Leetcode
  
• Pramp
  
• Github
  
• Mindsumo
  
• Kaggle
  
• Bitbucket

Start early. Like, really early. Think about starting your search at the end of your junior year and working with us over the summer. Many students have their post-graduate business position solidified in September or October. 

Check out the industry recruiting timeline for more information.

TigerLink: CC's alumni online directory and professional networking platform compatible with LinkedIn

• The directory allows you to search for other alumni, and your inquiry can be as general or specific as you like using the advanced filters section. You can send a message to other alumni through the directory, too.
• The mentoring component empowers students and recent graduates to connect with alumni who can assist in exploring careers and industries. Alumni can choose to connect with students in a variety of ways as well as expand their own professional network and advance their careers through connections to insiders who work for top employers.