Tons of proactive data enthusiasts spend hours, days, weeks and even years to learn the science of data, also known as, data science. However, it just seems odd that their professional portfolio isn’t getting them a call back from the organization they wanted to work at. If you fall into the same category, this article is aimed at helping you land your first data science job in Nepal.

How To Get Your First Data Science Job in Nepal?

But first, let us point out why you may not get your first data science job anytime soon if you aren’t prepared enough.

Issues with the data science job market of Nepal

An aspiring data scientist is usually as optimistic as an entrepreneur is with his/her new startup idea. However, the market decides whether an idea succeeds or fails and the same goes with the data science job market.

Here are some of the things that you need to know before applying to a data science job.

  1. There are only a handful of companies doing data science in Nepal

This is the biggest obstacle that lies ahead of you. There aren’t just enough organizations in Nepal (specifically Kathmandu) posting data science vacancies in comparison to the people who need data science jobs. This means that the general population has caught onto the data craze way before the companies have and the supply is blowing out of proportion to the demand.

AI companies in Nepal - The Click Reader
AI Company Logos: Fusemachines, Kharpann, CloudFactory (Left to Right)

The Click Reader has listed out the top 10 AI companies in Nepal who have been known to put out data science vacancies in the past. Following them on social media might be a good idea to know which positions are open.

2. A thousand other people are learning the same course as you are

In Nepal, most aspirants learn their data science skills from Massive Open Online Courses (MOOCs). This means that most graduates learn similar data science skills and competition is fierce since everyone is mostly competing with the same amount of knowledge.

A thousand other people are learning the same course as you are

Learning from a MOOC is fine as long as you are able to specialize your knowledge into a particular domain. A guy doing Natural Language Processing (NLP) for the past 6 months has more chances of getting into a chatbot development company than a guy doing computer vision for the same amount of time.

If you do not have any unique skills, your typo-free portfolio may not even get you short-listed. Keep this in mind if you apply to a company that works mostly in a particular domain.

3. Product-based companies tend to recruit data analysts rather than AI engineers

Do you wish to start building a production-ready neural network on your first day at work?

Well, you should know that getting into a product company in a data science role does not necessarily mean that you will be building a neural network anytime soon. This turns into an issue sooner or later for most Deep Learning fanatics.

Product companies in Nepal
Product Company Logos: Tootle, Khalti, SastoDeal (Left to Right)

It is important to understand that Nepalese digital products are coming at a place where their systems are finally integrating CI/CD techniques into their workflow. Building NNs at this stage is not only impractical for them but also not a good return on investment. Thus, it may be hard for you to gobble this fact down if you are unaware of it early on.

However, if you stick long enough at your company, you’ll certainly be able to try different avenues on your own lead given that your motivation doesn’t go away by then. But, if you are eager to get your hands dirty early on, you should aim at getting a job in an outsourcing-based company that does AI projects for foreign companies.

4. Businesses prefer data science personnel who are comfortable with business lingos

Nice job learning all the classification and regression techniques but have you ever thought that you may now have to learn what KPIs, ROI, Breakeven point, etc. mean?

Business Lingo

Knowledge of basic business lingos is becoming more and more necessary each passing day because businessmen want to hire people with good soft skills on top of their hard skills. This is because businesses see people in data science roles as creative and decisive individuals who can take a good business decision based on mathematics and statistics.

Hope the heads up given above will be handy to many. Now, let’s move onto how you can actually get a data science job in Nepal that you can love and commit to.

The guide to getting your first data science job in Nepal

Sorry if the above issues demotivate you about your chances. However, a true entrepreneur never quits and thus, neither should you.

The following guide has been put out in a step-wise fashion for you to have an easier time reading.

Step 1: Follow all known data science company and their C-suite executives across all social platforms (especially LinkedIn)

Companies put out vacancies when they need someone to fill in a role that feels missing. Thus, they put out such call-outs across social media. If you have information that someone is hiring, you can learn more about them and write your cover letter like you had been waiting for that vacancy all your life. Quality over quantity.

Follow all known data science company and their C-suite executives across all social platforms (especially LinkedIn)

LinkedIn is a special place for you to do this since C-suite executives are themselves sharing vacancies. However, you should apply for it through the mailing address rather than messaging them with your portfolio since that brings on a sign of desperation and we do not want to give that impression.

Step 2: Programming language selection – Learn R and Python in conjunction

Most companies prefer hiring aspirants who know Python but who have also tasted programming in R. This is good to have for companies since it shows that the aspirant is open to learning new languages and frameworks (such as Tensorflow or PyTorch) to get the job done.

Learn R and Python in conjunction

But, keep your basic knowledge of R at about 20% and Python at about 80% before sending in your portfolio. Knowledge of R is good to have but knowledge of Python is a must to have in most cases. Furthermore, your portfolio should show that you are very comfortable working with the following libraries:

  • Python: Numpy, Pandas, TensorFlow/PyTorch, Scikit-Learn and Matplotlib.
  • R: GGPlot

Step 3: Start playing with data as much as you read about it

As mentioned earlier, data science is a field of science and it is impossible to know everything. So, slow down on learning the theories and start applying them.

Your work portfolio speaks more about you as an aspirant than any other medium. Thus, you should have links to published papers, research blogs or open-source data science projects at a bare minimum. This allows hirers to know your thought process, your tool of choice and your approach to solving problems.

Kaggle logo

To start off, pick a competition on Kaggle that seems interesting to you. Go to the public kernel section of the competition, find the highest-ranking kernel doing EDA (Exploratory Data Analysis) and go through the author’s thought process. Now, take a deep breath and work on the competition by yourself and share your kernel publicly. It usually takes about 4-5 competitions by the time you finally start doing note-worthy work.

Your chances of landing your first job will certainly go up when you have proofread Kaggle kernel links on your portfolio that explains your thought process as well as domain knowledge. Bonus points if your kernels are from the same domain as the company you’ve applied at.

Step 4: Tailor your portfolio based on the job description and not based on the title

Job titles are usually kept to be more lucrative than what they really are. Read the job description carefully and understand what the role is about without looking at the title.

Tailor your portfolio

For example, a trend seen in the HR industry right now is that companies generally receive more applicants when they put out a vacancy for a data analyst rather than business intelligence analysts. Thus, a title may fool you into a job that you wouldn’t want to apply at or don’t have the knowledge for.

The list below shows you the actual title based on the job description keyword:

  • Should be able to use SQL and handle ETL processes – Data Engineer
  • Should be able to extract quality information from available data – Data Analyst/Business Intelligence Analyst
  • Should know SQL and handle ETL processes, build robust AI systems and extract quality information from all kinds of data – (A three-in-one Data Scientist)

Step 5: Be patient and keep applying

The best things come to those who wait.

Be patient and keep applying

If you have put your time into doing your homework and sending tailored cover letters and a well proofread portfolio displaying your work, you should get a positive reply back soon. Wait and work on your skills in the meantime.

Step 6: Appear your interview as a human being and not as a robot

You’ve done it. You’ve received that good news of being shortlisted and now, only an interview separates you and your new company from finally being together. Btw, if you still need to appear a coding round for a data science position, may god help you with it since we can’t.

Appear your interview as a human being and not as a robot

Interviews are generally the same across all fields of work and your confidence and knowledge are put at a test. If you think you can do it, you will.

Here is a video talking about the different data science interview questions you may be faced with along with their answers:

In Conclusion

We know that we may have induced fear, excitement or even nervousness when you went through the article. But, you certainly now know how to land your first data science job in Nepal and we wish you the very best.

Also, if you are interested in reading more data science related articles, here is a recent article that shows the case study done by Kharpann on Foodmandu using data science. Happy reading!



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