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How to get entry level data science jobs for bootcamp grads

Hi, I’m Olga! I have years of experience in data science, most recently at eBay and now I work as an industry mentor at Pathrise, helping data scientists land a great role through technical workshops and 1-on-1s.

Students enrolled in data science bootcamps hope to land an entry level job after graduating. But, hundreds of people will be applying for the same open roles, including recent university grads who have spent 4 years studying data science, statistics, computer science, and other data-centric fields. Many recent grads even have internship experience at top tech companies. As a bootcamp grad, how can you grab the attention of recruiters and hiring managers? 

Based on our experience helping aspiring data scientists land their dream jobs, we have compiled a list of top tips and suggestions so you can move forward with your applications and interviews with confidence.

1. Strengthen your resume and online profiles

You need to ensure that your resume, LinkedIn, and GitHub profiles are strong before applying to any jobs. Instead of using grunt statements on your resume, which demonstrate what tasks you did, focus on impact statements, which use numbers to quantify results and show how and why your accomplishments made a difference. You can also describe the scale of a project by including information such as how many devices you served, how many tests you considered, how many scenarios you handled, and more. This gives additional context to your work and helps tell the story of your experience in a more clear narrative.

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To help paint a fuller picture of your previous work experiences or projects, you can optimize your LinkedIn by expanding on the information you included in your resume. Your LinkedIn profile should have links to your GitHub profile and additional projects as well. This way, recruiters can access all of your previous work in one place. 

Finally, you should not underestimate the importance of a data science portfolio when applying for jobs. To remain competitive on the job market, both bootcamp and university grads should spend substantial time working on side projects, which they can upload to their GitHub portfolios. Be sure to include context for that work, so recruiters and hiring managers can better understand your passions and skills. 

Besides uploading new projects, you can also contribute to existing GitHub repositories and projects. By actively working on your portfolio, you can help differentiate yourself from your peers, who will be applying to the same job postings with similar portfolios. Finally, side projects allow you to highlight your strengths, collaborate with other data scientists, and practice skills that were not covered in your bootcamp’s curriculum.

2. Find the jobs and positions that match your skill set and experiences

As a data science bootcamp grad, you should recognize what roles match your specific skill set so that you apply for the right job to kickstart your data science career

In general, data science bootcamp grads have 4 options: data analyst, data scientist, data engineer, and business analyst. Those prepared for data analyst roles should have backgrounds in collecting, organizing, interpreting, and creating reports using data. In addition, they should be ready to perform analysis and assist with making effective business decisions by using tools such as SQL, XML, Javascript, and R, as well as machine learning programs, data visualization tools, Hadoop, and more. 

For data scientist jobs, you need to be proficient in Python, Java and R (the most common data science programming languages) in addition to having advanced skills in math and statistics. They use advanced mathematical and algorithmic techniques to solve complex problems, build analytical tools, identify trends, propose solutions, and more. Proficiency in MATLAB, SQL/NoSQL databases, SPS, and SAS is crucial.

Those interested in data engineer jobs generally have backgrounds in fields such as software engineering, computer science, and information technology. You might begin your career by looking for IT assistant or management roles. Duties include building and maintaining data pipelines and warehouses, developing and constructing architecture with databases and large-scale processing systems, solving problems using different scripting languages, statistical modeling, and more. Besides mastering the standard data science programming languages, data engineers should be proficient in UNIX, Linux, Solaris, AForge.net, as well as Bigtable, Cassandra, Ruby Perl, C/C++, and more. 

If you have experience working at the nexus of data and business, you can consider business analysts positions, especially if you have a background in business administration, finance, or accounting. Business analysts use diagramming programs, data analysis programs, Hadoop, and SQL/NoSQL databases to evaluate and develop strategic plans for businesses. They must be comfortable using business model analysis, process design, systems analysis, as well as communicating with colleagues, management, the IT department and other stakeholders to help reduce costs and create & test new systems. 

3. Reach out to hiring managers, recruiters, and fellow bootcamp grads

Writing a good cold email to recruiters, hiring managers, and fellow bootcamp grads can help draw attention to your application and can often be the factor that moves you forward. You can use LinkedIn to find the recruiters and hiring managers who will be evaluating your resume and portfolio.

Try connecting with people who have something in common with you. Sharing an interest or growing up in the same city are good starting places, but you will probably have better luck reaching out to someone who attended the same bootcamp as you. They are more likely to offer assistance, as they will have a stronger understanding of your background. You can find an email address using tools like Clearbit and Leadfinder. If you prefer to add someone as a connection on LinkedIn, always include a personal note that highlights your connection and expresses your interest in their current position or company.

Another option for bootcamp grads is networking with fellow alumni through the bootcamp’s career center. Reach out, introduce yourself, and let them know that you are actively looking for a job. If you are already familiar with the career center, don’t be afraid to update them on your job search. Often, they will direct you to companies that currently employ their graduates. In addition, most bootcamps have alumni groups on Facebook, LinkedIn, Slack, and other online platforms, which can be excellent spaces for sharing job resources and networking.

4. Research the company to prep for behavioral interviews

As you prepare for phone screens and behavioral interviews, you need to develop a strong understanding of a company’s culture, as well as their values, mission, and products. You might have a Facebook account that you use everyday, but you should still research the company before interviewing. Take a look at their About page to see their mission and history, which can help you understand their goals, achievements, values, and more. Facebook, for instance, includes a page that advocates for promoting safety and freedom of expression. You can mention this value, which is one of the company’s main priorities, in your elevator pitch and your responses to their behavioral interview questions to emphasize why you are a good fit with their culture and mission.. 

Photo of how to answer behavioral interview questions for Facebook

You can use our list of behavioral questions from top tech companies to start thinking through how you would personalize your answers. 

5. Study key concepts and work through mock technical interview questions

As a bootcamp grad, you might have spent less time working with data than students from other backgrounds. To prove that you are ready for an entry level data science position, you need to perform well on your technical interview. 

When you prepare, be sure to read practice questions carefully. You don’t want to start solving the problem until you understand each component. When you tackle a mock interview question, brainstorm some clarifying questions you would ask the interviewer before beginning, like “For how long did you collect the data?” or “What does this unit represent and why?” 

Interviewers want to understand your logic and reasoning skills, so you should practice explaining your process as you solve mock interview problems. Almost all of the questions on your technical interview will test your knowledge and understanding of the following areas:

  • Statistics
  • Probability
  • SQL/databases
  • Programming
  • Modeling
  • Specific case studies

Carefully study these fundamentals so that you develop a thorough understanding of each one.  

To help you get started, we have compiled a list of data science interview questions from top tech companies

6. Brainstorm questions for your interviewer

Another way to prove that you have an in-depth understanding of the data science field and the company to which you are applying is by preparing questions to ask in a data science job interview. Posing thoughtful questions helps you demonstrate an understanding of the tools and methods that data scientists use, as well as underscore why you are excited about the company’s work culture, values, and products. 

By using our suggestions and tips, you can prepare to take the necessary steps to land a job in data science. If you are interested in optimizing your job search by working 1-on-1 with a mentor and receiving additional guidance on each step of the process, join Pathrise.

Apply today.

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