What Do Recruiters Think of LinkedIn Recommendations

What's Recruiters' opinion of LinkedIn Recommendations Numerous enrollment specialists discover LinkedIn priceless. As indicated by information gathered in 2013, 89% of scouts have utilized the expert system to fill a position. Something that selection representatives take a gander at on LinkedIn is the proposals area of a forthcoming activity up-and-comer. Not at all like the a single tick abilities supports on LinkedIn, a suggestion is a composed proclamation of proposal from an association. From a selection representative's perspective, this composed proclamation could give important knowledge on an occupation applicant's capacities. In any case, not all proposals are made equivalent. Counterfeit suggestions: As the idiom goes, you can't believe all that you read on the web and hence, most scouts comprehend that they can't confide in all LinkedIn proposals. They understand that a few suggestions are composed by accommodating loved ones and are probably going to do a little examination concerning where the proposal has originated from and how genuine it truly is. Most enrollment specialists can detect a phony suggestion pretty without any problem. Here and there they may get some information about the dubious suggestions during the meeting, while different occasions they may simply ignore that competitor. So making fakes truly arent worth the time or exertion by the day's end. Dubious proposals: Some LinkedIn proposals are extraordinary, anyway others can be a bit too dubious. For example, John was a delight to work with and took care of business. This is an exceptionally positive suggestion, yet it seems like a great many different proposals and at long last, it loses its effect. It doesn't inform the enrollment specialist much concerning the activity competitor's capacities aside from that he took care of business, which is commonly the base desire for a worker. Proposals that feature explicit accomplishments or how the individual has helped the association/others holds significantly more worth and gives planned bosses a thought of what the up-and-comer would conceivably have the option to accomplish for them. Magnificent suggestions: What most selection representatives search for on LinkedIn are one of a kind and point by point suggestions. For instance, proposals that discussion about an occupation competitor's qualities, how the activity applicant coexisted with other colleagues, how the activity up-and-comer defeated issues at work, and so on. Suggestions with models are shockingly better. For instance, John supported deals by 47% in one year is substantially more impressive than John expanded deals. While the nature of LinkedIn proposals matters, who they are from is similarly significant. Having five explicit suggestions from genuine customers are worth in excess of 20 general proposals from colleagues. It's impossible that LinkedIn proposals are supplanting reference-checking at any point in the near future. Be that as it may, they do give enrollment specialists an increasingly all encompassing perspective on work applicant. Consequently, you ought to consistently approach individuals you have worked with for suggestions. You can be key about it and propose specific encounters or abilities that you might want them to feature. Request that they evaluate their proposals by including explicit models since explicit quantifiable models are more eye-catching than some tasteless and nonexclusive proclamations. Picture Credit: Shutterstock

Dont Forget The Hidden Talent Pool - People with Disabilities - Workology

Don’t Forget The Hidden Talent Pool - People with Disabilities - Workology Despite a jobless rate that has been at roughly 8% or higher for four years straight, recruiters at many companies have complained that they have jobs to fill but no good people to fill them. While there are acute talent shortages in key employment areas, such as nursing and advanced manufacturing, across many markets, hiring managers have overlooked a key talent pool for many skilled positions. People with disabilities make up roughly 15 percent of the U.S. working-age population, yet their participation rate in the workforce is roughly 1/3 of their non-disabled colleagues and their unemployment rate is nearly double their non-disabled counterparts. 22 years after the passage of the Americans with Disabilities Act, the employment picture is little changed for this group, which includes people with visible disabilities such as cerebral palsy or paraplegia, as well as hidden ones, such as individuals with ADD, Aspergers or certain types of Multiple Sclerosis. There are many reasons for this; here are a few of them: Corporate recruiting practices make it difficult for many people with disabilities to get hired. Disabled job seekers can fall through the cracks when job descriptions cite “requirements” that are not needed for the job, but which only serve to exclude people with disabilities, such as driving requirements for computer programmers; online applications that do not meet Internet standards for accessibility; and hiring managers who lack the training to effectively interview candidates with disabilities. People with disabilities have less well-formed professional and social networks. This is caused by a number of factors: Less time at work due to fewer job opportunities; more time in school to avoid to the challenge of work; and a lack of formal and informal mentors with disabilities who can offer their expertise to the younger generation. Expectations for people with disabilities are set by others, not themselves. For example, I know an engineering graduate with high-functioning autism who is dissatisfied with the profession that was chosen for him by his well-meaning parents, as well as the career opportunities his school pushed upon him. Unable to focus on his true passion for filmmaking and science fiction, this individual goes from one engineering job interview to another, and, with each passing rejection, sinks into greater and greater despair. People with disabilities are a hidden talent pool that can provide a much needed skill set boost to the recruiting department. Once hired, they will also likely offer a unique perspective on the company’s business that could shed new light on current opportunities, or even suggest new markets to be explored. Companies which fail to embrace people with disabilities risk being left behind not only by missing out on some great talent or business opportunities, but also by being out of touch with some of their younger non-disabled workers who went to school with people with disabilities and therefore expect to be working with them as well. ABOUT THE AUTHOR Adam Kaplan is the Founder and CEO of Big Tent Jobs, LLC (www.bigtentjobs.com) a Michigan-based recruiting agency which places talented technical professionals, including those with hidden and visible disabilities, in positions at leading companies. Adam was recently appointed by Michigan Governor Rick Snyder to serve on the Michigan Council for Rehabilitation Services. He can be reached by calling 877-366-6562 or via email at akaplan@bigtentjobs.com.

How to Write Submissions for The New Yorker Magazine

Step by step instructions to Write Submissions for The New Yorker Magazine Step by step instructions to Write Submissions for The New Yorker Magazine The New Yorker magazine was established in 1925 by Harold Ross. Ross cleaned his scholarly cleaves at day by day gatherings of the well known Algonquin Round Table, of which he was a sanction part. The clever Dorothy Parker and Robert Benchley added to the magazine in its initial years and were additionally individuals from that scholarly legend. The magazine has genuine abstract status. All through the twentieth century, getting your work distributed in The New Yorker was a significant achievement, and the magazine keeps on being one of the most loved distributers of short fiction. Composing Legends Grace Its Pages The magazine has offered perceivability to and helped make the professions of such effective scholars like John OHara, John Cheever, John Updike, F. Scott Fitzgerald, Raymond Carver, J.D. Salinger, Janet Frame, Salman Rushdie, and Alice Munro. In spite of the widespread decrease in magazine readership since the introduction of web based distributing, The New Yorker (under the administration of supervisor David Remnick) keeps on flourishing, bragging more than 1,240,000 perusers. The New Yorker Style In spite of the fact that the magazine has contributed too much of short stories to the scholarly ordinance, that doesnt mean all that it distributes is traditionalist. The magazine has likewise taken risks on some genuinely trial journalists like George Saunders and Haruki Murakami. What that implies for you, the author, is that regardless of whether your work veers toward the less conventional, don't hesitate to give it a shot. Sally will consistently accept that she knew without a moment's delay even before she heard Peter's voice, she realized what had occurred. On the off chance that a mishap had occurred, it would not be to her six-year-old, who was daring however not innovative, not a hotshot. From Deep-Holes by Alice Munro. Chances of Getting Published The chances of getting distributed here, obviously, all rely upon what your identity is. On the off chance that youve distributed nothing, the chances are incredibly, thin that youll get distributed dependent on space accessibility. The New Yorker distributes just a single story for each issue (giving one issue for every year to new fiction). All things considered, about each driven American author attempts to get into The New Yorker sooner or later. What's more, while the magazine takes risks on new journalists, it will in general draw from its stable of built up essayists, similar to Munro and Murakami. All things considered, if youre one of the youthful authors the magazine takes a risk on, on the off chance that your work is acknowledged, at that point your profession is made, so its value making an effort. How to Send Submission Present your story as a PDF connection utilizing the magazines online entries structure. Email your accommodation to fictionnewyorker.com. Send each story in turn and permit three months for a reaction. Entries can likewise be sent by normal mail to Fiction Editor, The New Yorker, 1 World Trade Center, New York, NY 10007. You will possibly get notification from the magazine in the event that it is keen on distributing your work. On the off chance that you have not heard inside a quarter of a year, you ought to expect your story has not been acknowledged.

Python Numpy Tutorial

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A technophile who likes writing about different technologies and spreading knowledge.1 Comments Bookmark 3 / 17 Blog from Python Libraries Become a Certified Professional In myprevious blog, you have learned about Arrays in Python and its various fundamentals like functions, lists vs arrays along with its creation.But, those were just the basics and with Python Certification being the most sought-after skill in the programming domain today, theres obviously so much more to learn. In this python numpy tutorial, you will understand each aspect of Numpyin the following sequence:What Is a Python NumPy Array?NumPy Arrays v/s ListNumPy OperationsNumPy Special FunctionsSo, lets get started! :-)What is a Python NumPy?NumPy is a Python packagewhich stands for Numerical Python. It is the core library fo r scientific computing, which contains a powerful n-dimensional array object, provide tools for integrating C, C++ etc. It is also useful in linear algebra, random number capability etc. NumPy array can also be used as an efficient multi-dimensional container for generic data. Now, let me tell you what exactly is a python numpy array.NumPy Array:Numpy array is a powerful N-dimensional array object which is in the form of rows and columns. We can initializenumpy arraysfrom nested Python lists and access it elements. In order to perform these numpy operations, the next question which will come in your mind is:How do I install NumPy?To install Python NumPy, go to your command prompt and type pip install numpy. Once the installation is completed, go to your IDE (For example: PyCharm) and simply import it by typing: import numpy as npMoving ahead in python numpy tutorial, let us understand what exactly is a multi-dimensional numPy array.Here, I have different elements that are stored in their respective memory locations. It is said to be two dimensional because it has rows as well as columns. In the above image, we have 3 columns and 4 rows available.Let us see how it is implemented in PyCharm:Single-dimensional Numpy Array: import numpy as np a=np.array([1,2,3]) print(a) Output [1 2 3]Multi-dimensional Array: a=np.array([(1,2,3),(4,5,6)]) print(a) O/P [[ 1 2 3] [4 5 6]]Many of you must be wondering that why do we use python numpy if we already have python list? So, let usunderstand with some examples in this python numpy tutorial.Python NumPy Array v/s ListWe use python numpy array instead of a list because of the below three reasons:Less MemoryFastConvenientThe very first reason to choose python numpy array is that it occupies less memory as compared to list. Then, it is pretty fast in terms of execution and at the same time it is very convenient to work with numpy. So these are the major advantages that python numpy array has over list. Dont worry, I am going to prove the above points one by one practically in PyCharm.Consider the below example: import numpy as np import time import sys S= range(1000) print(sys.getsizeof(5)*len(S)) D= np.arange(1000) print(D.size*D.itemsize) O/P 140004000The above outputshows that the memory allocated by list (denoted by S) is 14000 whereas the memory allocated by the numpy array is just 4000. From this, you can conclude that there is a major difference between the two and this makes python numpy array as the preferred choice over list.Next, lets talk how python numpy array is faster and more convenient when compared to list. import time import sys SIZE = 1000000 L1= range(SIZE) L2= range(SIZE) A1= np.arange(SIZE) A2=np.arange(SIZE) start= time.time() result=[(x,y) for x,y in zip(L1,L2)] print((time.time()-start)*1000) start=time.time() result= A1+A2 print((time.time()-start)*1000) O/P 380.9998035430908 49.99995231628418In the above code, we have defined two lists and two numpy arrays. Then, we have compared the time taken in order to find the sum of lists and sum of numpy arrays both. If you see the output of the above program, there is a significant change in the two values. List took 380ms whereas the numpy array took almost 49ms. Hence, numpy array is faster than list.Now, if you noticed we had run a for loop for a list which returns the concatenation of both the lists whereas for numpy arrays, wehave just added the two array by simply printingA1+A2. Thats why working with numpy is much easier and convenient when compared to the lists.Therefore, the above examplesproves the point as to why you should go for python numpy array rather than a list!Moving forward in python numpy tutorial, lets focus on some of its operations.You may go through this recording of Python NumPy tutorialwhere our instructor has explained the topics in a detailed manner with example s that will help you to understand this conceptbetter.Python NumPy Tutorial | NumPy Array | Python Training | EdurekaPython NumPy Operationsndim: You can find the dimension of the array, whether it is a two-dimensional array or a single dimensional array. So, let us see thispractically how we can find the dimensions. In the below code, with the help of ndim function, I can find whether the array is of single dimension or multi dimension. import numpy as np a = np.array([(1,2,3),(4,5,6)]) print(a.ndim) Output 2Since the output is 2, it is a two-dimensional array (multi dimension).itemsize: You can calculate the byte size of each element. In the below code, I have defined a single dimensional array and with the help of itemsize function, we can find the size of each element. import numpy as np a = np.array([(1,2,3)]) print(a.itemsize) Output 4So every element occupies 4 byte in the above numpy array.dtype: You can find the data type of the elements that are stored in anarray. So, if you want to know the data type of a particular element, you can usedtype function which will print the datatype along with the size. In the below code, I have defined an array where I have used the same function. import numpy as np a = np.array([(1,2,3)]) print(a.dtype) Output int32As you can see, the data type of the array is integer 32 bits. Similarly, you can find the size and shape of the array using size and shape function respectively. import numpy as np a = np.array([(1,2,3,4,5,6)]) print(a.size) print(a.shape) Output 6 (1,6)Next, let usmove forward and see what are the other operations that you can perform with python numpy module. We can also perform reshape as well as slicing operation using python numpy operation. But, what exactly is reshape and slicing? So let me explain this one by one in this python numpy tutorial. reshape: Reshape is when you change the number of rows and columns which givesanew view to an object. Now, let us take an example toreshape the below array:As you can see in the above image, we have 3 columns and 2 rows which has converted into 2 columns and 3 rows. Let me show you practically how its done. import numpy as np a = np.array([(8,9,10),(11,12,13)]) print(a) a=a.reshape(3,2) print(a) Output [[ 8 9 10] [11 12 13]] [[ 8 9] [10 11] [12 13]]slicing: As you can see the reshape function has showed its magic. Now, lets take another operation i.e Slicing. Slicing is basically extracting particular set of elements from an array. This slicing operation is pretty much similar to the one which is there in the list as well. Consider the followingexample:Before getting into the above example, lets see a simple one. We have an array and we need a particular element (say 3) out of a given array. Lets considerthe below example: import numpy as np a=np.array([(1,2,3,4),(3,4,5,6)]) print(a[0,2]) Output 3Here, the array(1,2,3,4) is your index 0 and (3,4,5,6) is index 1 of the python numpy array. Therefore, we have printed the second element from the zeroth index. Taking one step forward, lets say we need the 2nd element fromthe zeroth and first index of the array. Lets see how you can perform this operation: import numpy as np a=np.array([(1,2,3,4),(3,4,5,6)]) print(a[0:,2]) Output [3 5]Here colon represents all the rows, including zero. Now to get the 2nd element, well call index 2 from both of the rows which gives us the value 3 and 5 respectively.Next, just to remove the confusion, lets say we have one more row and we dont want to get its 2nd element printed just as the image above. What we can do in such case? Consider thebelow code: import numpy as np a=np.array([(8,9),(10,11),(12,13)]) print(a[0:2,1]) Output [9 11]As you can see in the above code, only 9 and 11 gets printed. Now when I have written 0:2, this does notinclude the second index of the third row of an array. Therefore, only 9 and 11 gets printed elseyou will get all the elements i.e [9 11 13].linspace This is another operation in python numpy which returns evenly spaced numbers over a specified interval.Consider the below example: import numpy as np a=np.linspace(1,3,10) print(a) Output [ 1. 1.22222222 1.44444444 1.66666667 1.88888889 2.11111111 2.33333333 2.55555556 2.77777778 3. ]As you can see in the result, it has printed 10 values between 1 to 3.max/ min Next, we have some more operations in numpy such as to findthe minimum, maximum as well the sum of the numpy array. Lets go ahead in python numpy tutorial and execute it practically. import numpy as np a= np.array([1,2,3]) print(a.min()) print(a.max()) print(a.sum()) Output 1 3 6You must be finding these pretty basic, but with the help of this knowledge you can perform a lot bigger tasks as well. Now, letsunderstand the concept of axis in python numpy. As you can see in the figure, we have a numpy array 2*3. Here the rows are called as axis 1 and the columns are called as axis 0. Now you must be wondering what is the use of these axis?Suppose you want to calculate the sum of all the columns, then you can make use of axis. Let me show you practically, how you can implement axis in your PyCharm: a= np.array([(1,2,3),(3,4,5)]) print(a.sum(axis=0)) Output [4 6 8]Therefore, the sum of all the columns are added where 1+3=4, 2+4=6 and 3+5=8. Similarly, if you replace the axis by 1, then it will print [6 12] where all the rows get added.Square Root Standard DeviationThere are various mathematical functions that can be performed using python numpy. You can find the square root, standard deviation of the array. So, lets implement these operations: import numpy as np a=np.array([(1,2,3),(3,4,5,)]) print(np.sqrt(a)) print(np.std(a)) Output [[ 1. 1.41421356 1.73205081] [ 1.73205081 2. 2.23606798]] 1.29099444874 As you can see the output above, the square root of all the elements areprinted. Also, the standard deviation is printed for the above array i.e how much each element varies from the mean value of the python numpy array.Addition Operation You can perform more operations on numpy array i.e addition, subtraction,multiplication and division of the two matrices. Let me go ahead in python numpy tutorial, and show it to you practically: import numpy as np x= np.array([(1,2,3),(3,4,5)]) y= np.array([(1,2,3),(3,4,5)]) print(x+y) Output [[ 2 4 6] [ 6 8 10]]This is extremelysimple! Right? Similarly, we can perform other operations such as subtraction, multiplication and division. Consider the below example: import numpy as np x= np.array([(1,2,3),(3,4,5)]) y= np.array([(1,2,3),(3,4,5)]) print(x-y) print(x*y) print(x/y) Output [[0 0 0] [0 0 0]] [[ 1 4 9] [ 9 16 25]] [[ 1. 1. 1.] [ 1. 1. 1.]]Vertical Horizontal Stacking Next, if you want to concatenate two arrays and not just add them, you can perform itusing two ways vertical stacking and horizontal stacking. Let me show it one by one in this python numpy tutorial. import numpy as np x= np.array([(1,2,3),(3,4,5)]) y= np.array([(1,2,3),(3,4,5)]) print(np.vstack((x,y))) print(np.hstack((x,y))) Output [[1 2 3] [3 4 5] [1 2 3] [3 4 5]] [[1 2 3 1 2 3] [3 4 5 3 4 5]]ravel There is one more operation where you can convert one numpy array into a single column i.e ravel. Let me show how it is implemented practically: import numpy as np x= np.array([(1,2,3),(3,4,5)]) print(x.ravel()) Output [ 1 2 3 3 4 5]Lets move forward in python numpy tutorial, and look at some of its special functions.Python Numpy Special FunctionsThere are various special functions available in numpy such as sine, cosine, tan, log etc. First, lets begin with sine function where we willlearn to plot itsgraph. For that, we need to import a module called matplotlib. To understand the basics and practical implementations of this module, you can refer Matplotlib Tutorial. Moving ahead with python numpy tutorial, lets see how these graphs are plotted. import numpy as np import matplotlib.pyplot as plt x= np.arange(0,3*np.pi,0.1) y=np.sin(x) plt.plot(x,y) plt.show() Output Similarly, you can plot a graph forany trigonometric function such as cos, tan etc. Let me show you one more example where you can plot a graph of another function, lets say tan. import numpy as np import matplotlib.pyplot as plt x= np.arange(0,3*np.pi,0.1) y=np.tan(x) plt.plot(x,y) plt.show() Output Moving forward with python numpy tutorial, lets see some other special functionality in numpy array such as exponential and logarithmic function. Now in exponential, the e value is somewhere equal to 2.7 and in log, it is actually log base 10. When we talk about natural log i.e log base e, it is referred as Ln. So lets see how it is implemented practically: a= np.array([1,2,3]) print(np.exp(a)) Output [2.71828183 7.3890561 20.08553692]Asyou can see the above output, the exponential values are printed i.e e raise to the power 1 is e, which gives the result as 2.718 Similarly,e raise to the power of 2 gives the value somewhere near 7.38 and so on. Next, in order to calculate log, lets see how you can implement it: import numpy as np import matplotlib.pyplot as plt a= np.array([1,2,3]) print(np.log(a)) Output [ 0. 0.69314718 1.09861229]Here, we have calculated natural log which gives the value as displayed above. Now, if we want log base 10 instead of Ln or natural log, you can follow the below code: import numpy as np import matplotlib.pyplot as plt a= np.array([1,2,3]) print(np.log10(a)) Output [ 0. 0.30103 0.47712125]By this, we come to the end of this python numpy tutorial. We have covered all the basics of python numpy, so you can start practicing now. The more you practice, the more you will learn.Got a question for us? 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Top 10 HR Interview Questions Answers (June 2020)

Top 10 HR Interview Questions Answers (June 2020) Top 10 HR Interview Questions Answers 2020 Image Source: iStockSo you’ve got a call for interview. Congratulations! Next step (although this is something you can always devote time to) involves  preparing  to present yourself as the candidate the recruiter is looking for. This will come down to how well you can respond to a fairly standard set of HR interview questions devised by human resources professionals. Of course, interviews are not everyone’s comfort zone, but don’t be derailed by nerves.It’s always best to devote some reasonable amount of time to your appearance and the overall image you want to convey. This is important whether you naturally incline to the strictly formal, or the more contemporary professional image that tends to blur the rigid boundaries of classic professional attire. If you’re bringing documentation or a laptop, dont carry these in a plastic bag!! Find yourself a quality briefcase or document holder on Amazon, where there are many to be found, for all tastes, and at reasonable prices: i ncluding Samsonite’s Classic Three Gusset Lg Toploader. If you don’t incline to such a formal look, you could opt for the sleekly casual (but still sharp) Vintage Canvas Satchel Bag  by  Life Boost,  or the MancroWater Resistant Polyester Laptop Backpack.Above all, please remember that the job interview is not a trap. These recruiters or HR interviewers want to meet you. Their questions are opportunities for you to set out how your skills fit the organisation. As stated, these questions are fairly standard. Don’t get caught out for want of preparation! (adsbygoogle = window.adsbygoogle || []).push({}); Preparing Responses to the top 10 HR  Interview QuestionsThese are the top 10 HR interview questions, with advice on what the interviewer is looking for with each, and tips on how to prepare answers.  When answering these  standard HR interview questions, be  brief, concise and to the point.The suggestions below are just thatâ€"guidelines  on preparing tailored answers  to draw from during an interview. For maximum impact,  personalise the  responses by illustrating with your own experiences.And even if you are asked a question you didn’t anticipate, don’t be flustered or defensive. Stay calm, and, using the advice on the questions in  this list, take a moment to think about what you are actually being asked, before you answer. (adsbygoogle = window.adsbygoogle || []).push({}); 1. “Tell me about yourself.”The interviewer does not want to know your life story! What they want to know is whether you’re a good fit for the position. Research your resume, and prepare an answer about yourself that describes your  qualifications, previous roles and skills,  emphasising the most relevant skills.2. “What have your achievements been to date?”Describe  a recent work-related achievement, identifying skills used and quantifying its benefit to your employer. For example, you  used graphic design  and marketing  skills to devise a social media strategy tha t has improved your company’s SEO ranking. Or, you  used your  IT skills to design and/or implement  a new system that has streamlined customer payments, improving the company’s debtor position and saving significant monthly sums on interest. (adsbygoogle = window.adsbygoogle || []).push({}); 3. “Are you happy with your career to date?”There is only one answer to this HR interview question, and that’s “Yes.” The question is designed to determine your self-esteem, confidence,  and what your professional aspirations might be. The best approach is to briefly explain why you are happy with your career. If you genuinely feel you’ve reached a plateau,  be prepared to explain why, and again, keep it positive, framing it in terms of your wish to stick to a long-term career plan or progression.4. “What’s the most difficult situation you’ve faced,  and how did you tackle it?”Image Source: iStock“Difficult” is subjective. This HR interview question is used for two things: to find out how you define “difficult”, and whether you have logical problem-solving processes. Again, keep things simple. Choose a difficult work situation that was not of your making, but which you helped to resolve satisfactorily. Use a brief 4-step description, outlining:How you identified the problem;Options that you considered for resolving  it;Which solution you chose and why; andThe outcome. (adsbygoogle = window.adsbygoogle || []).push({}); 5. “What do you like about your present job?”Again, the key to answering this HR interview question lies in your own resume. The model response should ensure that what you like tallies with the essential skills listed in the specifications for the role advertised. It’s important to strike a balance here. Okay, you want to be positive and enthusiastic, but not so much as to provide an opening for a “So why do you want to leave?” question!6. “What do you dislike about your present job?”Tread carefully. This HR in terview question is a bit of a trap, and a very easy one to fall into. You want to stay away from  specifics that might expose your own weaknesses, and definitely avoid be negative towards individuals. Go ‘macro’ with your answer. Focus on a big-picture characteristic, such as the size of your present place of employment, or the slow speed of its decision-making processes. Maintaining a positive, can-do, take-it-in-your-stride demeanour is the key here. (adsbygoogle = window.adsbygoogle || []).push({}); 7. “What are your strengths?”Image Source:  PixabayAnother  of the HR interview questions that is certain to be asked, there is no excuse for anything other than a meticulously prepared answer. Think about three to four general ‘headline’ aptitudesâ€"for example,  determination focus; positive attitude; collaborative team skills; ability to learn qualityâ€"and  think of specific examples to illustrate these proficiencies when asked during the interview. To repeat, of al l HR interview questions, this one is a sitter, so be prepared!8. “What is your greatest weakness?”Another of the HR interview questions that, along with greatest strengths, is almost guaranteed to arise. The key advice  is, do  not say that you have none! Everyone has weaknesses. So do one of two things. Either  speak about a weakness or shortcoming that’s not vital for the job (such as lack of experience); or, describe a weakness that  might also be considered a strength, and talk about what you do to keep it in check. So, you might have forensic attention to detail that serves you well, but can also be  time-consuming, so you must devise your own rigorous timelines for every task. Also, your high standards sometimes may make your team think you’re too demanding, but you always try to keep a balance between carrot and stick and encourage as much as direct. (adsbygoogle = window.adsbygoogle || []).push({}); 9. “Why do you want to leave your current employer?”As with  N umber 6 on this list, the response to HR interview questions such as these should always be positive, never negative. Do not focus on personalities or individuals. And don’t say that your primary motivation is salary. Keep it simple; express your response in terms of seeking a new challenge with greater responsibility.10. “Why have you applied for this particular job?”Image Source:  iStockLast on our list of HR interview questions, but by no means least… in fact, it may well be the first thing you are asked. Through your response to HR interview questions like this one, you should be using specific points from your resume to emphasise that the role  is a good fit for your general and specific skills, that it fits with your career progression and long-term goals, and that you will enjoy it. Again, preparation is the key. Undertake research about the business generally, and drill down into the specific role to ensure that you understand its position within the organisation, so that you can fluidly discuss things about the company and the position that particularly interest you.