As the Great Reshuffle or the Great Resignation creates a volatile labour market, one can find more opportunities than ever before. When the job market is so elastic, it’s crucial not to be swayed by shiny perks or huge paychecks, and to evaluate and accept only the best offers. Especially in a new field like Data Science, it can be difficult to evaluate the true intent and merit of an offer. I’ve rounded up the 3 most important questions every Data Science job candidate should consider asking before accepting that lucrative offer.
This is one of the most crucial things to keep in mind while evaluating an offer, and often this information is not very clearly defined in the job description or even during screening calls. Some of the best data-driven companies hire people for solving specific problems in teams with a clearly defined goal. No matter if it is a new team hiring their first data person, it is important to clarify what they expect this person to accomplish.
What questions does it help you answer?
- Do they have a S.M.A.R.T goal?
- Is the problem defined by the company solvable by hiring a data person?
- Do they have the requisite data collected and the infrastructure ready to undertake such a project?
- How mature and data-driven is the company?
Most hiring managers should be able to answer this question easily. If that’s not the case, then there are some obvious red flags because as a data person you are expected to maximize business success based on certain KPIs. As with the above question, you get a feel for how mature the company is in regard to developing data-driven strategies and setting measurable targets. Often, job descriptions and hiring managers use very generic KPIs like “maximizing revenue and customer satisfaction” which is not bad, but it is very generic. As a data person, it allows you a very narrow vision of what type of influence you can have within the company once you join.
What questions does it help you answer?
- What kind of impact can you bring about by joining this company?
- Is this KPI one of the most crucial ones playing into the Business success of the company?
- Are the leaders in the company data literate enough?
In many cases, this is one of the most important questions to ask, because oftentimes you think you will be a part of a team until you realize you are the team. This can be avoided by asking questions about the team size, how old the members are, and who will be your supervisor. By evaluating the organizational structure of the prospective team, you can also choose your working style, career growth path, and perhaps mentoring opportunities. Data scientists in service-based companies deal with clients rather than fellow colleagues. This is in contrast to a product-based company, where they work in cross-functional teams. Making a decision can be complicated if you don’t know how a company collaborates and communicates.
What questions does it help you answer?
- Is this a collaborative or an individual contributor role?
- Who are the stakeholders and how does one report to them?
- How often do people engage in knowledge sharing or brainstorming?
As you ask these questions, you not only make a better decision but also position yourself as a bright, knowledgeable candidate for the recruiting team. The answers to these questions will not only clear up many of your doubts but will help you decide which type of company would be right for you as well.
