Creating a resume for applying to data science jobs can be underwhelming for most of us. Companies need to look at the resume of a pool of candidates as preliminary screening before shortlisting the right ones for an interview. A resume is basically a brief summary of your educational qualifications, job skills such as AI and Machine learning, and relevant work experience. LSET is a reputed data analyst training centres in London, we have a deep knowledge of the data science industry. We also know how a professional Python developer is hired in the job market. We have put together some tips and tricks to help you build a strong and professional resume that will catch the attention of a recruiting manager.
Keep the Resume Brief
The first tip towards creating a professional resume is to keep it brief and to the point. A brief resume would allow recruiters to focus on the important information without making them work hard to understand your background. An ideal resume should only be one page long. Whether you are a python developer, data scientist, or data analyst, you must prioritise the information you wish to put into your resume.
Customise your Resume Based on the Company and Job Description
Many people create a single resume and send that to every data scientist job where they are applying. However, it would be a good practice to make some customisations in your resume for every application you submit. Adding a few small details based on the job descriptions and organisational background will impress the AI and Machine Learning recruiter.
Data Science Projects
The most important thing on your resume after your name and contact information are the projects you have completed as a data scientist or a python developer. You should highlight your projects which might include data analysis projects, machine learning projects, etc. However, showcase only the relevant projects. Select the projects that demonstrate your technical skills and how your skills can be used to solve real-world business problems.
Highlight Your Skills
Be specific about the skills, tools, and technologies you have used to create projects in the past. Mention additional skills such as python developer or machine learning expert. Recruiters often use keywords search to source resumes, and highlighting relevant and allied skills of data science will help you get noticed quickly. Learn new skills with data analyst training and make your resume even more professional for data science jobs.
Education and other Qualifications
Although educational qualifications or a degree is a must in most companies, it is better to list your projects and skills before your educational background. Apart from your college degree, you can also list additional certifications such as short-term data analyst training or a machine learning certificate. Alternatively, you can also showcase your certifications under the projects or skills section in a rather implicit manner.
Become a Proficient Data Scientist at LSET
Achieve your career goals as a data scientist with comprehensive learning and real-world experience at LSET. Our data analyst training offers students a deep understanding of the tools and technologies used in data science, AI and Machine Learning. We provide convenient learning formats and a hands-on approach to the students and make them job-ready, and we also cover everything from basic Python and SQL to deep learning technologies. Call our data science experts today to learn with the best faculty at LSET.