Here, we’re going to focus on a very important part of the analytics interview process: what the hiring manager is looking for in an analytics candidate. We know how stressful the interview process can be so we hope that, by knowing a little more about the hiring process itself, you can adjust your approach to the interview to get the best chance of success.
First, we are going to explain the general types of questions you can expect in an analytics job interview. Then, we’ll take a look at five crucial factors that a good candidate should have.
What Can I Expect From an Analytics Job Interview?
In an analytics job interview, they expect you to be able to code well, obviously. By this point, you should have experience with the type of coding language they are evaluating and have the data analysis skills to handle whatever they throw at you.
You will likely encounter a use case during the interview, which is basically a scenario that can sometimes be complex, requiring multiple steps and solutions for you to solve. Often, this is based on a problem the company has experienced or is currently experiencing.
Obviously, they expect you to attempt to solve this problem but it’s equally important for you to explain how you got your solution. They are evaluating your process and approach. How you arrive at your solution is just as important as the solution itself.
5 Factors that Analytics Interviewers Look For In Candidates
We mentioned that the main thing to expect during an analytics job interview is that it is about the process. There are so many ways to solve a problem in analytics that keeping open communication with the interviewer and explaining how you reached each decision and how you are going to handle each use case and edge case is crucial.
Keeping an open mind is a key factor in this interview process. You must evaluate each question with the willingness to consider each available option. This is crucial to even identify the problem you are trying to solve.
Your goal is to have a healthy conversation with questions and answers that demonstrates to the interviewer that you have considered all the options. By doing this, you also have a better chance of putting yourself in the position to choose the best option.
2. Structured Thinking
As explained above, analytics interviewers are looking for someone open-minded and willing to consider all available alternatives before choosing the best one. This shows an understanding of the math and the theory behind what you are trying to do. Communicating your process and explaining how you approach the data are important for the interviewer to understand your analytical skills.
In order to effectively communicate, you must develop a pragmatic and structured line of thinking in approaching the problem. This way, no matter what problem you face, you have a structured method to show the interviewer exactly how you approached the solution.
Questions can often involve analyzing lines of codes. Be careful to look at the syntax and explain what each block of code is achieving. From there, identify a “big picture” for what the code is achieving and identify what could be added to or removed from this code to reach a solution. By following this reliable process, you ensure that the interviewer can easily follow your thought process. And you ensure that nothing is missed on your end.
3. Closing the Edge Cases
Edge cases are one of the most important parts of understanding an analytical problems. With any problem you encounter in an interview, try to think of any edge cases where the code could break and communicate that to the interviewer. In addition, identify edge cases where certain situations in the business problem might not be captured in your solution. Then build a solution to capture those edge cases. Suggest ways that they could be accounted for so that a given situation will not break the code. This is much easier to do because you identified the potential problem areas first.
4. Understand Trade-Offs
In technical interviews, there is almost always more than one way to analyze the data and solve a problem which raises the inevitability of trade-offs. You might have to forgo one method to pursue a different one. In your interview, the most important thing to do in this situation is to identify these trade-offs then explain each option and why you may or may not chose one over the other. This should be a conversation with the interviewer so that your solution is optimized for the business goal.
Your solution is probably not going to be 100% perfect but if you communicate why you chose one option over the other and why you think your solution is ideal, the interviewer will be satisfied with your problem-solving skills and analytical abilities. These are the things that interviewers are often most interested in evaluating.
5. Explain What the Solution Will Give You In A Way That Is Easy For Anyone To Understand
Once you are satisfied with your thought process and your solution to the problem, it is important to wrap it all up. A great way to do this is by providing a summary of your solution to the interviewer. Remember, the most important thing to get across is that you understand the problem, what you’re trying to achieve, and are willing to evaluate all the options to reach a solution.
So, wrap up each answer with a summary. Quickly explain your solution, the options you considered, the trade-offs, the edge cases, and why you believe your solution is the best. This ensures that the interviewer comes away with an understanding of your thought process.
You have probably noticed a common theme throughout these points. In these technical interviews it’s about about showing your understanding of the concepts and the ability to think critically and pragmatically rather than reaching the correct solution to a question. The right answer is really only a piece of the puzzle. Analytic interviewers approach the interview process with the intention of hiring someone who approaches each problem with an open mind and a willingness to consider every alternative.
These qualities represent a candidate who will not only think strategically but is also not afraid to work with others or ask for help. After all, companies want to hire someone they can work with and you need to prove that you have the communication skills and insight necessary to do just that.
If you want some practice with technical problems and want to see how others have approached the same problems, try some of the technical questions in Strata Scratch and review the approach and solutions from their users.
Today we’re going to focus on one of the most important parts of the recruitment process and the one that is probably the most feared: the technical interview. Your first interview (other than the screening call with the recruiter) is usually the technical interview, which is sometimes done over the phone with a screenshare. If you do well there, then you’re often invited to the second round, which may contain multiple technical screenings. There are many tips for success in the interview process, in fact, we have written interview preparation guides before. Check one out here. That said, you’re often nervous, sweating, and not thinking straight. It’s important to not only know what to do, but to also know what not to do (i.e., sort of like when you take a driving test at the DMV -- you can do everything right 99% of the time, but there are just some things that will automatically fail you, like hitting the curb).
Here, we’re going to give you our top six tips for what not to do during a technical interview. Let’s get started!
1. Do not immediately start to codeOne huge thing to note right off the bat is that analytical interviews are not just about finding the right answers. The interviewer is testing your ability to solve a problem which includes your ability to ask questions and use problem-solving skills to gain an understanding of the question or questions behind the question being asked.
To demonstrate this skill set, you can’t just start coding as soon as you receive the question or coding challenge in an interview. First, you should ask clarifying questions and state assumptions to demonstrate that you understand exactly how to solve this problem. The interviewer wants to see your process to make sure you understand the best way to approach the problem.
Even if you feel confident about the problem and don’t have any questions, you should communicate that to the interviewer. They want someone who is confident in their understanding of the problem before they begin coding. So, don’t just start coding right away – stop, ask questions, and demonstrate your understanding.
2. Don’t brush off the interviewer’s hints
Often, an interviewer gently nudges you in the right direction. Ultimately, they want you to succeed so they might drop hints or ask questions to lead you toward the solution. This is why it is so important to consider everything the interviewer says in the interview and not to brush off or gloss over their comments.
If they say something like, “What about the denominator in the ratio…” or, “Have you taken a look at this metric…”, then you need to think about that and apply it. In probably all cases, they wouldn’t have said it if it wasn’t relevant.
3. Don’t be too opinionated
One of the top skills that an interviewer is looking for is the ability to adapt. Don’t be someone with strong opinions who is unwilling to budge. You should demonstrate the ability to consider different options and adapt your approach when new information is present.
Be aware that job interview questions might be designed to test this. By presenting new information, the interviewer checks to see whether you can reflect on what you have done, recognize any errors, and adapt. Often, this skill is just as important as finding the right answer as it represents your ability to continuously work to get there.
Don’t be too opinionated. Go into the interview with a flexible and open mind.
3. Don’t accept the most obvious answer Analytics job interviews are supposed to weed out a certain proportion of interviewers. If they made it too easy, they wouldn’t be getting the best people for the job. This often means that the answer to the technical questions is not going to be the most straightforward, obvious one. After all, these questions are there to test your skills.
What interviewers are looking for is someone who carefully examines the questions and considers all the available alternatives and understands trade-offs. What does this mean for you? You should walk them through your decision-making process. Show them that you are considering each option and considering how each variable might affect your answer. This way, even if you do not reach the correct answer, they can see that your decision-making process is sound.
Do not accept the most obvious answer. Often, the answer is meant to seem obvious to trick you. Interviewers will not be satisfied if you do not give each option proper consideration.
4. Don’t talk about how you’re unqualified because you don’t have formal education in a technical field.
The fact is that not everyone working in analytics has a technical background. There are many ways to learn analytic skills that do not involve a formal education. Many people in analytics do not have a technical background but, through hard work and dedication, have achieved the skills necessary to do these jobs and do them well.
That said, if this applies to you, you should not draw attention to this fact - it’s not relevant. You are there and you have the skills you need to do the job so drawing attention to the fact that you are perhaps less qualified than those with a formal education is not going to help you get the job.
In an interview, you only need to bring something up if it is relevant to your ability to succeed in the role. If you are asked about your formal education, do not hide details but there is no need to bring it up if you aren’t required to.
5. Don’t talk about how you’re qualified because you do have a formal education in a technical field.
On the flip side, do not talk about how extremely qualified you are because you have a formal education in analytics. Likely, the interviewer already knows this based on your resume and mentioning it, again and again, can come off as bragging. At the end of the day, the interviewer doesn’t care about your formal education, they just want to see if you have the skills necessary to do well.
This interview exists to test your skills, after all, not to check up on your formal education. Focus on showing them what you can do, not talking about your degree.
It’s always a good idea to be prepared but it’s just as important to know what not to do in certain situations. We hope our tips have helped you in your preparation for your technical interview.
If you take one thing from this list, remember that these interviews are about the process. Even if you don’t think you can get the right answer, walk them through your decision-making process and show them that you are willing to accept all alternatives. A person who approaches the work this way is bound to get the right answer eventually, which is what they really want to see.
With advancements in technology and most of the population having access to the internet, there is no denying that data analytics has become a hot topic in recent years. The data analytics job opportunities landscape looks promising and ranges to several industries, in fact, the nature of work often allows flexibility of working remotely or even self-employment. Besides that, even at the entry-level jobs the median salary for a data analytics job is quite high. According to a study, it is predicted that in the US alone 2.7 million job postings are estimated by 2020.
As more and more organizations are recognizing the importance of Big Data as a source to gain insights and make strategic decisions, the demand for skilled people in data analytics is increasing manifolds. Keeping this in mind we have compiled here some of the best data analytics job opportunities in the market today.
However, before we begin, let us take a brief look at the skills that will be required for a job in data analytics.
Most of the positions in the field of data analytics require the same foundation skills so the key is to master these before you start posting your resume to potential employers.
Python- This is one of the most commonly used programming languages. You may look up for an online Python tutorial to learn the basics of Python. It is important to have a solid understanding of how to use Python for data analytics even if is not a required skill in any job position since it will give you an upper hand in the job market. Though most of the online Python tutorial gives basic knowledge, however, you should also look for advanced programming proficiency to learn analyzing and manipulation of data. Also, understand the concept of data collection, web scraping and start building web applications.
SQL- Having a basic knowledge of SQL is often required for data analytics job roles. When going for an interview always go through SQL interview questions which are often asked by hiring managers. You can get the basic knowledge of SQL through a SQL tutorial online. Just like Python, SQL is also a relatively easy language to learn and the basic knowledge of SQL will take you a long way in your career.
Here are the few job opportunities worth looking into-
IT Systems Analyst
The required level of expertise differs in these positions thus creating opportunities for specialization by personal interest and industry. The system analysts design and use systems to solve problems in IT.
As a data engineer, you will be designing and implementing data infrastructure. This position is a step up in complexity, however, it’s your skill, knowledge, and preference that will be the deciding factor.
Healthcare Data Analyst
The healthcare data analysts can help doctors, scientists by finding answers to the problems and questions they encounter on a daily basis. With the growing amount of data in the health industry coming from the popularity of Apple watch or advanced medical testing in clinics, labs, and hospitals, the demand of data analysts in the sector is on the rise.
If you like working with big data frameworks or creating dashboards or like analysis or querying of data then this is a perfect job role for you.
Operation Analysts are typically found internally at big organizations but they may also work as consultants. The key responsibility is to focus on the internal process of a business. The professionals need to need to be general business savvy and also need to possess technical knowledge of the systems they work with. So from large grocery chains to military services, opportunities are many.
The professionals need to have fluency in programming to statistical and querying capabilities to managing, extracting, and designing to conducting initial exploratory analysis. Data Scientists also need to figure out the machine learning algorithm that will help in performing predictive analysis, visualizing the results and presenting it to the management.
This is one of the most sought-after job roles, especially in the financial sector. Data analytics is used to seek out risk management problems or potential financial opportunities. A quantitative analyst can venture out on his own to create trading models to predict the price of commodities, stocks, etc.
Digital Analytics Consultant
The primary responsibility is to deliver insights into a company to help in business. As a consultant, you can work for different companies in a small period of time.
Besides the above, you can also work as Project Manager, Digital Marketing Manager or Transportation logistics specialist if you have a data analytics background.
These were just a few of many high-paying jobs, the salaries may differ according to the city/country and the general cost-of-living expenses.
With a boom in artificial intelligence, data science, and machine learning applications, the demand for Python developers has also increased. Python’s ease of access and readability has made it one of the most popular programming languages today. Switching over to Python can unleash endless possibilities for developers. Here, we have identified some of the most important Python concepts which you should know.
Most online tutorial courses assume that you need to learn all syntaxes in Python before you start doing anything interesting. This may lead to spending months only on Python syntax when what you want to be doing is to analyze the data or build a website or maybe create a drone!So here are the 7 Python concepts that you need to focus on besides the Python syntax while you take up an online Python tutorial-
Variables- object types and scope
Information that can be used for a program is stored in variables and they typically have a name so that they can be referenced in the code. Python supports strings, numbers, lists, sets, tuples, and dictionaries which are standard data types. If you check any online Python tutorial you can read in detail about these data types.
In Python, if you have to declare a variable, you only have to assign a value to it. There is no need for any additional commands. Variables can have local or global scope. One of the most common Python questions asked in an interview is – Mention what are the rules for local and global variables in Python?
Therefore, ensure that you know this concept thoroughly as it forms the basis of your programming.
It allows the user to perform computation on variables. The following are the different types of python operators.
Comments are used to make the code more readable. It helps in explaining the Python code and can also help in preventing execution when testing code. Comments in Python start with a ‘#’. It can be placed at the end of a line, and the rest of the line will be ignored in Python. You can refer to online Python tutorial for usage of comments in detail.
Loops in Python
Repetitive commands or redundant codes can be a nightmare for any programmer. Python uses loops to overcome this problem. The loops allow you to execute a group of statements numerous times. Loops in Python are categorized as –
Sets and dictionaries in Python are almost identical, except that sets do not contain values actually, it is just a collection of unique keys. Sets are used in doing set operations whereas Python dictionary is a collection that is changeable, unordered, and indexed. The items in a Python dictionary are accessible by referring to its key name.
Therefore, learning the concept of Python dictionaries and sets is essential. If you are taking up an online python tutorial then do learn about Python dictionary with methods, functions, and operations. There are a few in-built dictionary methods in Python which can help you in programming.
Classes and Functions
Python is an object-oriented language, therefore it is important to know the concept of classes thoroughly. A Python class is like a blueprint of an object that provides all the standard features of object-oriented programming. The classes can have custom attributes/ properties and functions. The object-oriented design allows the programmers to define their business model as objects with their required functions and properties.
On the other hand, functions in Python are a sequence of statements that you can execute in your code. It helps in eliminating the repetition of code and make it simpler to debug or find issues. Most importantly, functions make the code more understandable and simpler to manage.
Slicing in Python is most commonly applied to lists and strings. It is a process of taking a subset of any data. To put it simply, slicing enables the programmer to choose what to see and focus on thus aiding in implementing abstractions and readability.
We hope that you find the above useful. To understand these concepts in detail do go through Python problem sets while you undertake a full-fledged online python tutorial.
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