I am going to provide very interesting and useful tips through this blog series which will help students to kick-start their career in Data.
There are lots of job profiles which are in demand in the market - data analyst/data analytics/data visualization/machine learning / deep learning/data scientist/software engineering in data analysis/data science/machine learning, big data engineer and many more. Titles may keep changing depending on your expertise in skills and work experience.
So, as lots of people are ready to dive their career into it, I am going to provide very interesting and useful tips through this blog series which will help students to kick-start their career in Data.
Kick start your career in Data Tip #1
Be an Explorer [In Academics] - Never limit your area when you are exploring & learning things. Stop worrying about GPA [Score]
I would say if you are enrolling yourself in masters or Ph.D. programs in any area - you are brave. You are showing the courage to learn and grow. So, what goes wrong after this step? Once you start studying, you get lots of assignments, lots of things to self-learn and explore, do work on research topics etc. Students start worrying about completing assignments On TIME to get maximum score, completing assignments 100% to get maximum score, completing assignment ACCURATE for maximum score. Which in turn counts towards their GPA. So, they start ignoring the fact of learning things and run behind scoring and getting good GPA. I would like to tell you if you are worried about getting maximum grades and for that, if you are asking somebody else's work to complete your assignment, this is going to give you nothing more than score. The consequences of it you realize when you start looking for a job. If you are maintaining your GPA equal to or greater than 3.0 [whatever standard, you have in your university], you are good to go. GPA doesn't matter, what matters is how much knowledge you gained. GPA is just a number, if you are having minimum criteria required to be eligible for applying to any job in the market, you are doing good. And if you follow the learning and gaining knowledge you will definitely end up scoring good.
So, don't limit yourself in exploring things during your academic years. Treat yourself as a blank slate and explore that area as much as you can within your academics. This is your time to explore being a new bee in the area. Don't hesitate to audit the courses apart from your required semester credits. The best part of universities here is you can audit courses for free. For that sometimes you may need to approach a particular professor to audit his/her class. You are gaining knowledge by auditing too. If you are not allowed to audit any class, I am sure you should be knowing someone else taking that class. So, approach and ask that friend about what's going in that class, what are they learning. This way you will get to know what's going on around. What skills are in demand in the market. What's going on in other areas too. Once you start exploring, you will get to know more and more about it and start getting to know your areas of interest too.
Talking specifically for data - take / audit maximum courses provided in your universities related to data analysis, data mining, machine learning, deep learning, data science, cognitive, data visualization, programming [ R, Python, Scala etc.], big data, business intelligence, probability, statistics, and many more. Don't just fall for completing credits, graduating and getting a degree. You are enough grown up to figure out what works for you. Try to find the time. Try to do your assignments your own. Don't worry about getting a score. If you want to really worry about something then worry about understanding concepts right, worry about utilizing your university time effectively, worry about helping yourself on time. So please, "Be an explorer!!".
Kick start your career in Data Tip #2
Take an advantage of facilities around - Be wise to utilize the facilities provided by University
Being enrolled in a university program you get lots of free facilities:
Free Wi-Fi [24X 7]
Open library [24 X7], access to lots of books and material
Free individual/group study rooms
Free access to lots of software and installation tools
Access to lots of technical events happening in the university [where employers come to present their case studies and what they are looking for
Visiting tours to some employers to understand their work culture
Take an advantage of each facility you are getting. You can learn and explore lots of tools free of cost. Group study rooms help you and guide on teamwork when you do your projects, prepare for your presentations. Visiting tours to employer's workplace gives you the motivation to work harder as it might be your dream job to get into it. It's not that due to these things you get into a job, but its understanding importance of each facility that university provides to you. It's up to you how you utilize those.
As we are looking for being an explorer, along with that it's important to take an advantage of facilities that the university provides to you. University programs don't restrict you to the particular subject, lots of these facilities are for you to explore and learn more.
Couple of you might not enjoy studying and learning all the time [ it's hard for everyone to be monotonous all the time], so there are couple more facilities which universities provide for your entertainment too like -
Cultural events and celebrations
Free pub or disc
Social Cause Activities like [END 7 initiatives etc.]
Game nights/ sports
Different clubs like hiking, rock climbing etc.
Make use of those too along with studies, but you are enough grown up to understand how much time you would like to spend on those. These non-technical events help you to make friends, have a social life, gives an opportunity to lead or organize some events. So, every facility you are getting has its own purpose. It's only your job to figure out the priority of each one of those. You are a student, and it's your job to take right advantage of any facility that the university provides to you.
Talking specifically to Data field, learn and explore maximum tools and software you are getting in university. Read books on stats, probability, mathematics, machine learning etc. Take the prints of book pages you want to refer in future too or write notes for your reference. Use group study rooms to discuss and understand your data. Do presentations. Attend company seminars or presentations to see their case studies. Join data clubs, if it's not there form one and organize events/meetings. Participate in competitions, it's easy to form a group in university as you will find lots of people having a common interest in your class. Take an advantage and be wise to utilize the facilities provided by University.
Kick start your career in Data Tip #3
Seek, Network and Showcase - Seek for groups/people, connect with people [University and beyond], showcase your talent/interest
Another very important aspect of getting into a field that you are interested in is "Seek for same passionate people, network and showcase your talent/interest". It's a hard but long and continuous process, needs to happen parallel with your education.
One aspect of networking within university we already talked about, but I will elaborate on that part a bit in this blog.
As universities hold and organize lots of technical events it's important to connect with people participating in the event. Not required to connect with everyone but important to initiate communication and showcase your passion.
Lots of employers visit the university campus to present their case studies, kind of work they are doing in their industry, it's important to meet and greet them, ask questions if you find something interesting to your area, and discuss your thoughts on it.
Sometimes universities shortlist the profiles and take some students to show work culture of a couple of employers, there too it's important to show courage, present yourself with confidence and build relationships.
Apart from University activities, there are other ways to do networking and connect with people. Like you can join technical meetups in data [ there are lots of available in every area], show up there, interact with people, ask them what they are working on, and show what you can to contribute. There are couple meetups run specifically to collaborate and work on Kaggle competitions, it's a great way to form group and work.
If sometimes you don't want to go for technical meetups, you can go for non-technical meets ups as well like gaming, hiking, movie clubs, Sunday brunches, those connections can turn into good and gives you more knowledge about the area you are trying to build your career in.
Apart from meetups, there are conferences like Open Data Science, Machine Learning, Robotics, and AI, Other university events - like MIT, Harvard etc. If you are not able to purchase the ticket, the advantage of being a student is these conferences promote students and provide them with discounts on tickets or you can join them to volunteer. That way you can again listen to and connect with lots of leaders and learn about their work in Data.
Participating in hackathons - This also gives you an opportunity to learn more creative work and allows you to participate and show your talent too.
So, what I feel is there are many ways you find, the only thing you require is to seek always what you are looking for. It's important to approach people and ask questions. Always keep in mind, no question is right or wrong, maybe sometimes it can be an easy one or a hard one. But never hesitate to find the answer by yourself or to ask someone. Never fall for finding any purpose talking to any person, you never know that contact can help you further in your career change. So, please "Seek, Network and Showcase".
Kick start your career in Data Tip #4
Be hardworking, persistent and patient - Always be persistent and have the patience to achieve what you want. Hard work always pays you back.
We talked a lot about, exploring, learning things, networking, showing knowledge or interest. Though the keywords sound very easy, it's a very hard and continuous process. Most of the people have a tendency to give up in between. I don't think it's their fault, but it's an attitude or a human tendency, where everybody needs or seeks a success and a fame overnight. The bitter part is, it never happens so. Always we see the success of a person but never see how long it took for that person to get that success or a fame. There might be some exceptions who became a billionaire in early age, but life wasn't easy for any one of them after that too, even though they achieved so much success, maintaining, digesting and further growing that success is an important factor.
As we know, the data field is in a boom right now, in the job market and there are lots of job opportunities/openings in a similar area, salaries are pretty fat too. No doubt, every individual wants to build their career into it. In result, it's a competitive field. And considering the kind of job application process we have, - it's not effective, it's almost outdated in turn people hardly get calls. Lots of profiles get filtered out with automated parsing system. So, students might find it challenging to get interview calls, but it's important to be patient and persistent. You should not lose your interest and patience if you are really looking to get into any specific job role. Keep applying to jobs through online job boards. People with whom you are networking always hand over your resume. It's important not to give up and if you don't then definitely you will get what you want.
Career change or technology change though they sound very easy, its easy on learning the part, but always hard on getting into that first job opportunity.
I do remember when I started my job search in Data science, my first concern was, why do they need Ph.D. candidates? How come degree can be a filter to any job role? How experience doesn't take priority over the degree? No doubt you are going to be in a similar situation now or later. But one very good quality I have is, " I never give up ". I was persistently applying to jobs - all the platforms - LinkedIn, Glassdoor or Monster [whichever you feel or all]. And finally got into one opportunity.
If you are getting your masters or Ph.D. in any specific area, it is required to work hard and get into the same area of interest. There might be more challenges being an immigrant or being new in that field, but definitely, these three qualities help to overcome those challenges. So, keep applying. It's not good to compromise before putting on efforts to achieve it. Be persistent & patient. I am sure things will work out for you one day, the way it worked for me.
Happy job hunting!
Kick start your career in Data Tip #5
Be outstanding - Find out your strengths and utilize those to be outstanding in any area you are interested to build your career in.
You might have heard from people you are meeting/networking/ approaching, lot more about being outstanding in the area you would like to build your career in.
So the general question - What I need to do, to be outstanding, to out-stand from other applicants who are looking to enter into data field? What should one have? Well, the answer is not straightforward, but definitely analyzing self-strengths and being creative & smart definitely helps to out-stand.
One needs to find out what he/she good at. It might be your writing, communication or leadership skills. Or you might be more innovative or creative. The answer to it is that every quality gives you an opportunity to be outstanding in the area you are interested in.
If you want to show that, yes, I have all the skill-sets required but something additional which makes my profile stronger compares to other applicants, it could be your blogging, it could be hosting and organizing meetups/ events, it could be public speaking, it could be doing your own projects. All these qualities definitely help you out-stand from any other normal job applicant.
So, remember every quality has its own glory and benefits, you need to understand how you would like to use that to build your career in any specific field.
Talking specific about data, you might find lots of people doing and using Kaggle projects, but you might believe and showcase your own interesting projects apart from academics to show your skills and creativity. You might find lots of people going to technical meetups, but adding value to those meetups, showing knowledge and sharing it, also holding and organizing those might out-stand you from others. You might find people following lots of leaders to gain knowledge, but there will be only few who believes in sharing knowledge and enhancing skills. The only thing you need to find out which side you would like to prefer to out-stand yourself.
I have seen lots of people changing their resume as per data job roles, does that really a need? The answer is maybe for automatic parsing system sometimes it is a need, but trust me, if you are good in any specific field or area, those obstacles don't affect much. Being creative at making your resume, is another separate topic, I will not go much in details for this blog, but rather than that important factor is "Finding out your strengths and utilizing those to out-stand yourself in the job market".