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7 min read · Feb 22, 2023
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By: Bella Chang, Lillian Jiang
Chances are pretty high that if you find someone majoring in Data Science or Economics at UC Berkeley, they will be majoring in the other field too, or know someone who is.
In 2020, UC Berkeley’s own Division of Computing, Data Science, and Society (CDSS) released a few facts related to this popular combo of interests:
- “Of the 950 declared Data Science majors, 17% are enrolled in the economics domain emphasis.”
- “Economics and Data Science is the most common double major — 40% of all students with multiple majors.”
- “Economics is the most common major, representing 24% of all Data Science minors.”
Intuitively, these two fields make sense together for someone looking to break into the workforce, especially within the Bay Area. A big aspect of the appeal of data science in industry right now is company-facing; a variety of companies need help understanding internal data, user data, and presenting data to their stakeholders.
Data Science Society decided to look more into a few of the most popular jobs that demand skills from these fields — Actuary/Risk Management Specialist, Company Growth Strategist, and Senior Data Analyst. Specifically, we interviewed a few of our alumni and other network connections to determine what exact skillsets are needed for these careers and how to prepare for these careers.
We asked our interviewees the same 3 questions:
- How was the interview process/recruitment like for your job? Would you say it’s a relatively high barrier to entry if you don’t have a DS/econ background?
- What kind of skills does a day in the life of your job require?
- What do you do that requires data science knowledge? Economics knowledge?
Question 1: Please describe the interview process for an Actuary/Risk Management Specialist. Would you say it’s a relatively high barrier to entry if you don’t have a DS/econ background?
“ 1) Initial screening with HR to discuss qualifications and resume 2) Technical screening on coding skills, data science questions to test my skills in programming, statistics, and machine learning 3) Behavioral interview to access company culture and teamwork fit 4) On-site interview: this is a series of on-site interview with members of the team to evaluate my technical skills, problem solving skills and communication skills.
There is a barrier to entry as fit and experience in data science and economists are required for an actuary/risk management specialist.”
Question 2: Please describe your skill sets for your daily work as an Actuary/Risk Management Specialist.
“1) Experience with data manipulation, cleaning, and visualization using Excel, Python, R and other programming languages 2) Statistical analysis and machine learning techniques 3) Hands on business problem solving”
Question 3: Give me an example of your daily work that requires data science knowledge? Economics knowledge?
“Both of these knowledges are used for hands on business problem solving. Economics is used to understand the context on business problems. Integrate python into excel using pyXLL to take advantage of Python’s speed and wide range of quantitative functionality, as well as Excels user friendly interface. Use build in probability functions like rand() or the risk software to coduct in-depth simulations.”
Question 1: Please describe the interview process for a Company Growth Strategist. Would you say it’s a relatively high barrier to entry if you don’t have a DS/econ background?
“The interview process for data science/BI/data analyst positions when I am hiring usually include some sort of skill assessment. Applicants are given data sets for them to create into reports, clean up, or analyze. After the assessments, the candidates go through multiple interviews that include managers from IT, Finance, and the Commercial business. You don’t necessarily need a Data Science degree, but it is helpful. You will need knowledge in the specific programming language required for the position. You don’t need to have a degree in DS or econ, but you need to have taken classes or learned programming or visual analytics tools, depending on the role.
For my role specifically, I did not have the typical interview process. I have worked at PE owned companies (all owned by the same PE group). I typically meet with the companies for them to tell me about their data and operational needs. I find out more about how their data is structured, systems they use, and meet with the team before I decide if it’s the right fit.”
Question 2: Please describe your skill sets for your daily work as a Company Growth Strategist.
“Good communication skills, attention to detail, ability to manage multiple projects at one time, working cross-functionally with all departments such as Marketing, Sales, Finance, IT, and Operations; being a strategic thinker as well as the ability to dive into the details, communicating with executive leadership on a regular basis, interpreting business needs into a technical requirements for IT, managing diverse personalities, ability to adapt quickly in rapidly changing environments.”
Question 3: Give me an example of your daily work that requires data science knowledge? Economics knowledge?
“I oversee the Analytics team, Integrations team, and Project Management team at my company. Analytics requires data science and econ knowledge. Integrations does too, because we work on integrating entire companies into our infrastructure, which will cover anything from accounting to operations to sales. All of these departments need analytics.”
Question 1: Please describe the interview process for a Senior Data Analyst. Would you say it’s a relatively high barrier to entry if you don’t have a DS/econ background?
“I would say that the interview process and recruitment for my past jobs are similar to all technical/specific field jobs. There is the general information about you, your skills and your past experiences in an open ended fashion to learn more about your self and your view of your strengths/weaknesses and experiences. There is then the more technical verification process that essentially validates that you have the skills that are required of the job (Think of this as a quiz to ensure you know how to think analytically and you know the hard skills). This will vary for what position you are applying to, i.e. a data scientist will need to know Excel, SQL and the basic tools that go along with it. Throughout the process it is essential to understand that not only are you being asked questions to make sure you will work for the company/position but also to understand that the company/position will work for you. I would say that the barrier to entry is similar to most technical/specific role jobs in that you either must have experience or education for the field. But if anything it’s a lower barrier to entry than most degree based jobs in the sense that there is so much information and education freely available to educate yourself that you can enter with less of a formal education than other fields.”
Question 2: Please describe your skill sets for your daily work as a Senior Data Analyst.
“I would say the most important skills are soft skills: the ability to learn and the ability to analytically think. But this said knowing the hard skill of coding and logic is needed but can also be learned if you have said soft skills. Also it is to be said that you must have the regular soft skills that every job/life requires: communication, empathy, organization, etc.”
Question 3: Give me an example of your daily work that requires data science knowledge? Economics knowledge?
“Most of my job (data analyst) requires data science knowledge. I would say the econ isn’t needed going into the job because it is easily gained while gaining understanding of the system, if you are in a role that is exposed to finance or the market (which I’d agree every job is).”
Key Points:
- The rise of the Data Science/Economics double major at Berkeley could be associated with the rise of the data science field overall. A big appeal of the data science field is to explain data and trends to stakeholders and businesses as well as take advantage of these trends to maximize profit and minimize risk.
- There are a variety of jobs that take advantage of the skillsets developed from this combo of studies.
- Even in a field that has a variety of different opportunities, there are some key differences between econ/data science jobs; both for barriers of entry and in the actual work being done.
Further Questions to Consider:
- Do any of these career paths interest you? How does your current studies in data science or economics affect your future career?
- What are some of the differences between the skillsets required for data science and econ jobs? What are the similarities? Are there any skillsets that you want to learn?
