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Make your tech interviews more humane

The interview process can invariably be perceived as a science of sorts - entailing discovery and requiring understanding at each step. From discovering a candidate’s technical proficiencies, striking up conversations that explore their breadth of knowledge and work, and unearthing their primary and secondary technology inclinations, it requires one to observe sharply, and experiment a lot along the way. One of the most important aspects of a technical interview involves gaining a birds-eye perspective of a candidate’s proficiencies and figuring how they fit-in with your organization’s requirements and goals.
Ironically though, the current state of process across most organizations sees that before a candidate walks into the interview room, they’re an idea for the recruitment managers. The way interviews usually pan out, ambiguity is often a dominant part of the entire technical interview process. Our traditional methodologies of pen and paper assessments, white-boarding, assessing theoretical concepts, and our heavy reliance on them to understand what a candidate is bringing to the table have watched themselves become fundamentally inefficient over time. Today, the tech industry evolves sporadically every day, and with it, watches the vast Indian tech talent pool evolve continually too.
With such continual transformations, recruiters could bring about a change to the face of interviews – with a backing of the right kind of information. Luckily, an availability of rich, insightful data isn’t a roadblock anymore. The key here is in discovering relevant information from the plethora of data that surrounds us. 
The following paragraphs attempt to draw out the changes that a data-driven technical interview can bring to the recruitment process, and how these changes can serve you with an objective and informed process. 

Lending a window to quality conversations

Every interview’s eventual goal is finding candidates whose proficiencies – technical and interpersonal, align with the organizations’ goals and culture. Should interview conversations be pieced keeping this goal in mind, the critical data-points in an interview would lend a lot of clarity to the team and help figure out what a candidate brings to the table in a more structured manner. 
Here are a few data-points that could lend a richer context and help shed the ambiguity from a technical interview's flow, while also enabling you to understand your candidates reasonably. 

A window into their experience on previous projects that sheds light on their primary inclinations and interest areas

This aspect, quite subtly, can act as a critical decision-maker in the recruitment process, primarily because – 
  • It helps you avoid misalignment of talent with the requirements of a job role at the most initial step. 
  • It ensures a proper alignment - helping you keep your talent driven and engaged with their job over a wider span of time.

Conversations circling a candidate’s past and present contributions across Social forums such as GitHub and Stack Overflow

Social platforms are one of the most consequential enablers towards discovering a candidate’s technical background thoroughly.

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For instance, a single glance at this GitHub profile would help you --

  • Observe your candidate’s work contributions over a period of time – thus opening a window to discussing and understanding their technical inclinations and projects in a crisper manner. 
  • Observe their activity patterns over a span of time as they make contributions to projects
  • Help you pin down their technical proficiencies from their contributions across projects
  • Also, platforms such as Stack Overflow help you understand your candidate’s problem-solving capabilities along with the breadth and depth of their technical knowledge basis their answers and accuracy.

Shifting from the dependency on a mere score towards conversations that revolve around technical efficiency 

Half the battle within a technical interview is lost the moment we begin gauging a candidate’s technical prowess based on their performance scores – when all the while, the aspect we need to be stressing on is a candidate’s technical efficiency.
Certain practical aspects such as the ones mentioned below would help map out their skillsets more realistically.

Understanding the types of coding violations that occur in a candidate’s solutions, and what it implies

To truly grasp a candidate’s technical efficiency – and not just their ability to scour through test cases, it is imperative to understand the implications that different kinds of code violations carry.

 For instance, observe the code solution after it has run through DoSelect’s engine -
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Our assessment engine points out the various forms of coding violations such as -
  • Complexity in the code
  • Vulnerability to bug risks
  • Vulnerability to Security issues
  • Improper code implementation leading to Performance errors

Adherence to the best programming practices in their solutions

Because - Writing maintainable code is one of the most important aspects of programming – as important as writing code that works.

A candidate’s code lends a wider historical context on their technical capabilities over a period of time. Some of the key particulars that our testing framework helps draw out from their code are – 
  • Understandability and usability of code
  • Adherence to a language’s style
  • Instances of duplication or redundancy in the code

Wider Historical Contexts that gauge a candidate’s technical acumen objectively and exhaustively

Quite like Rome, no good programmer became one, overnight. Neither did contemptible practices of programming change themselves for the better in a day.  The best way to understand the quality of a developer’s code is to observe its evolution across a time span.

Some of the best resources that help you gauge such evolutions are social forums such as GitHub and Stack Overflow. GitHub gives you a wider perspective on a candidate’s work and contributions over a period of time, an insight into the frequency activity, their best and worst coding practices, and their grasp on concepts based on their contributions and popularity (for forums such as Stack Overflow).

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DoSelect’s Crunch ties in a candidate’s social profiles. By putting together relevant information about a candidate’s technical contributions across GitHub, Stack Overflow and DoSelect. 
Insights such as these serve as conversations that help them relate and understand to the work they’re being interviewed for. As is always the case, a data-driven perspective is equipped with clarity, and the power to make informed and sensible decisions – decisions devoid of subjectivity. At DoSelect, we strive towards imbibing our tech sphere with this understanding every day. 
What are your current technical assessment blues? Write to us at and we would help you eliminate them in a cost-efficient and technically exhaustive manner. In case you want to give these assessments a spin, write to us at and we would set up a conversation.
Till next time. 

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