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Data Science Blog > Community > Job Search: 6 Proven Tips for Aspiring Data Scientists

Job Search: 6 Proven Tips for Aspiring Data Scientists

Terence Cortez
Posted on May 14, 2020
The skills I demoed here can be learned through taking Data Science with Machine Learning bootcamp with NYC Data Science Academy.

Job searching has always been a challenging process, and during the current economic slowdown, it may even seem unfathomable. But regardless of all that has changed, it is possible to enter the data science job market provided you take a comprehensive approach. In an effort to help you in your socially distanced job search, we gathered some first-hand advice from practicing data scientists. Check out these 6 tips for navigating your job search - during this time - and beyond.

1. Develop a strategy

With all the work involved in a job search, the process itself can feel like a full-time job. You can make it easier on yourself by developing a strategy that identifies the type of company you want to target, discovering what kind of role you want to land, and understanding the resources you have available to get there.

Leneve Ong, Data Scientist at Apple shares; โ€œThe job search is a slow grind. It can really take months, and there is a lot of prep that needs to happenโ€. Beginning your search by creating a detailed strategy provides you with a strong foundation to build upon. By identifying the required resources and your desired outcomes right off the bat, you effectively outline a clearer path for your search.

If things donโ€™t bode well in the first few weeks, having a job search strategy also allows you to look back at your initial vision, and adjust or pivot your approach according to what has proved successful, or unsuccessful in your initial efforts. โ€œTreat it as a data science project where you always iterate your approach whenever necessary,โ€ says Roger Ren, Data Scientist at Amazon. By having an iterative approach, you will be able to easily pinpoint your weakness. If youโ€™re noticing that you are not getting enough phone interviews after submitting countless applications, it might be a good idea to take a step back and spend some time enhancing your resume and cover letter.

โ€œThe majority of the time, a machine screen will screen your resume. Expand on your resume or more specifically, the way you describe your previous experiences by using keywords from the job description,โ€ says Ren. Itโ€™s always a great idea to spend an extra minute or two tailoring your resume to the job description of the position you are applying for. This allows you to emphasize on previous experiences that mirror the needs and priorities of the company.

2. Lean on your job network

Itโ€™s no secret that many jobs are found through networking rather than traditional job searching. A recent survey found that even though most applicants apply for jobs on a job board or employer career site, 35% found job postings on social media, 50% of respondents heard about jobs from friends, and 37% say they also learn about jobs from professional networks.

During your job search, make sure to lean on the network you already have. Reach out to the professional connections that are relevant to your job search, like colleagues from previous employers, classmates and other alumni from your school, and LinkedIn connections. โ€œDonโ€™t be afraid to reach out to your alumni network,โ€ says David Levy, Data Analyst at FanDuel.

Most feel limited to their current circle of friends and colleagues. It is helpful to also pay attention to your second-tier connections. Don't let fear stop you from introducing yourself to someone in proximity to your current network. If your messaging is direct and shows interest in simply connecting/discussing ideas rather than asking for a job or referral right off the bat, you are more likely to develop deeper and more personal connections that may benefit you either now or in the future.

When you learn how to leverage your alumni network in the right way, it can pay dividends by opening more doors and creating meaningful introductions to employers.

3. Get creative

It goes without saying that job searching today requires you to be more creative and open-minded than ever before. Finding a job might be harder if you have tunnel vision. It is important to be open to positions outside of the specific role or title you want. Most applicants search for a specific job title, however, you need to be prepared to think about your expertise more broadly. Be open to exploring function-adjacent positions with responsibilities that align well with your experience and interests. Limiting yourself to a narrow job title likely also limits the number of jobs you are applying to. Cast a wide net! You may be surprised by the way tangential roles can not only capitalize on your existing skills, but offer you an opportunity to grow in areas you had not considered before!

โ€œExpand your search and donโ€™t limit yourself to the title of data analyst or data scientist. There can be a wide range of job titles that you are qualified for. Especially during these times, having a broad range of job titles to consider can be a good thing. For example, look at other titles such as Machine Learning Engineer, Data Engineer, Research Scientist, or Business Intelligence Engineer. Fundamentally, they are all linked to the field of data science,โ€ says Ren.

4. Learn relevant new job skills

โ€œWhen I graduated in โ€˜09, it was the depth of the recession. It was a pretty scary time. I really wanted to gain some experience so I scoured the internet for any type of opportunity,โ€ says Ong. Searching for a job in tough economic times can easily put you in a downward spiral if you only concentrate on aspects you cannot control like, โ€œWhen will I hear back from Company X? When will the worst be over? Will I ever find a job?โ€

Since we cannot predict these things, your best strategy is to focus and take action on what you can control. Think about what you can do today, or during the next month, two, or three. Your job search is likely going to take time and how you choose to use that time is important. Make yourself an even better candidate by actively working on yourself. Strengthen your foundations by brushing up on your existing skills or determine what new ones you need to learn to make yourself more relevant.

โ€œStudy and fill in the gaps in your knowledge. There are more things that you know you could study or work on and if you donโ€™t know, work with someone else and figure out where those gaps might be. Reinforce what you know by working on projects to exercise your existing skills. Know the details that went into the experiences that you had. Ultimately, this gives you confidence in the interview process as you have a better understanding of what it is you did in the previous projects and how you can use those same skills to contribute to your new employer. โ€ says Ong.

These days there are plenty of online programs and courses that can help you develop new skills to help you stand out from other candidates. The key is to find the right program that can help bolster your qualifications to ensure that what you know is strong enough and will be relevant in the long run. If youโ€™re not sure where to start, check out these classes on data analysis and visualization, machine learning, and big data.

5. Donโ€™t go at it alone

Even in normal times, the job search process can be a pretty lonesome and isolating experience. Today, it is even more challenging. The easiest way to keep yourself optimistic and engaged is by finding friends and partners you can ask for help and who can hold you accountable. They can provide motivation, supply a referral that can get your foot in the door, or work with you to brush up on your data science skills or polish your application and portfolio.

โ€œFind a study friend. The most valuable thing for me was I had a group of close friends from when I joined the NYC Data Science Academy bootcamp that were able to collaborate with me during my job search. We practiced machine learning programming with each other as we prepare for technical interviews,โ€ says Ren. By having people around to bounce ideas off, you will be able to practice on technical questions and challenges through conversations with your peers, which in turn will help you during your next interview.

6. Create a healthy job routine

Before you start working on your job search, itโ€™s important that you put you and your essential needs as your top priority. This entire process is likely going to be a long journey so creating a routine that looks after your health and well-being first is imperative to stay on track.

โ€œWhen I was looking for a job, I lost hope many times. I was ready to give up and just go back and do some research work. I had this big interview that I thought went well; two of the interviewers even responded to me on LinkedIn. But eventually, I found out that I didn't get the job. It really hit me hard. I learned that when that happens, you just need to take some time off and relax,โ€ says Ren.

It seems obvious, but when you prioritize your overall well being, you develop the level of perseverance that can get you through the toughest of times during your job search. Levy shares, โ€œStay positive. Itโ€™s easy to say but hard in practice. Be confident in your skillset and the value you can bring to the table, put in the time and effort, and the right opportunity will come along. Itโ€™s just a process.โ€

In times of chaos, anxiety, and uncertainty, itโ€™s normal to be discouraged from developing a strong job search. But undertaking even a few of these pieces of advice from data science professionals in the field will improve your chances of landing a job that you love.


Quoted in this article are Leneve Ong, Roger Ren, and David Levy. Leneve Ong is a data scientist at Apple where she works on Siri and related artificial intelligence and machine learning projects. Roger Ren is a research scientist at Amazon working on automatic speech recognition and natural language processing for Amazon Alexa. David Levy is a data analyst at FanDuel. Both Roger and David attended the data science bootcamp at NYC Data Science Academy.

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Terence Cortez

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