A Brief About Data Scientist & Resume
Every domain has some designation that people aspire for and in order to attain that job position, there are a number of things that they need to perform. When it comes to the field of Data Science that job position is often considered as Data Scientist. To become a Data Scientist one requires a deep understanding of various theoretical and applicative aspects of it. This understanding is attained after long hours of labor that includes reading books, going through tutorials, long discussions with people involved in this field, etc.
While this knowledge is important, there is one more aspect of Data Science-related knowledge which is less discussed i.e. the knowledge of writing a Data Scientist’s Resume. A Data Science resume in India or a Data Science resume to target Indian companies requires understanding the job market and the requirement of the companies.
Resume play a very important role in the process of securing a job. A resume allows a candidate to showcase their discipline-related knowledge, past experience, inquisitiveness regarding the job position among other things. This allows the employers or HRs to decide whether the candidate holds those skills that are required for being considered for the job.
As the resume acts as the preliminary screening for any candidate, it can be considered as the ticket for getting into the whole interview process for any job position. Therefore, informed decision making is required while preparing the resume.
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Expert Tips to Write a Data Scientist Resume
Resume for a Data Scientist is a very important thing as it allows for the immediate screening of a candidate. While the article aims to get into the detail of the various aspects of writing a Data Scientist resume. There are some quick tips one must remember and follow while writing a resume such as-
- A typical resume must have a length of 1 or 2 pages at max. Do not write long extremely detailed resumes. On average HRs and employers spend less than 30 seconds on a resume.
- Use simple fonts. Do not use fancy fonts and styles.
- Use as many pointers as possible. Avoid providing detail in paragraphs.
- Use appropriate margins and spaces as this makes the resume look neat and easy to read.
- Write a different resume for different job positions as the background of the company should be considered in the resume.
- Use headings and sub-headings in different font or format (bold, italics, etc)
- Provide personal details such as name, phone number, email id.
- Provide URLs to your LinkedIn id, Github repository, personal website, and other social media profiles if have material related to the domain.
- Keep things formal. The language shouldn’t use phrases like “stuff like that”, “etc. etc.”. Also, provide an official email id that consists of your name or name and date of birth as a user name.
- Do not use a lot of colors. Resumes are often printed on black and white printers so using a lot of colors especially light colors can do more harm than good.
- Keep the information in a chronological manner. A typical format includes first explaining your profile in brief 3-5 lines. Then proceeding towards the education section, current job, work experience, college projects, independent projects, extracurricular information. Keep the important sections on top. Thus if the academic section is not related to Data Science, it’s better to push it towards the end of the resume.
- If have any reference, mention it.
- List your past achievements in the field of Data Science.
- Do not write complicated lines. Try to get rid of complex jargon and use simple words and if possible use creative verbs.
- Proofread your resume. Make sure there are no grammatical or spelling mistakes.
Important Tips With Explanation
There are some general tips for those who are creating a resume for trying to get a job of a Data Scientist or its related designation. While the generic tips have been mentioned in the above section, here more explanative tips to enrich the data scientist’s resume.
Focus on Professional Experience
For candidates who have work experience, past professional work is considered one of the most important aspects of securing a job. Under the section of job experience, from the latest to the oldest, all the work experience should be mentioned. It’s generally better if the job experience is related to the field of Data Science. The experience should tell the story of the growth of your knowledge and experience and how each job contributed towards your understanding of Data Science and achieving your career goals. Under each experience, there should be mention of the problems that were faced by you and how those problems were solved and eventually how this understanding helped you in solving other seemingly unrelated business problems.
Description of the Technical Skills
The knowledge of various tools related to Data Science holds a center stage in this field. The resume must showcase all the tools that you know. For example, a candidate must mention all the known programming languages such as R, Python, and should further mention the various libraries that are commonly associated with performing routine data science-related tasks. The mention of the libraries should be related to the job description. For example, if the job requires a lot of data manipulation in python then the mention of packages such as Pandas and NumPy is a must whereas if the job description is regarding solving text-related problems then packages such as NLTK, GENISM should be mentioned.
Description of the Theoretical Knowledge
Data scientists should be aware of the numerous algorithms and ways of approaching problems. This information must be provided as this will make the employers aware of the algorithms that you know and how this can help in accomplishing the tasks that will be encountered during the job. Again, an informative attempt must be made while listing out the name of known algorithms. For example, if the job description is regarding the prediction of values to solve the strategic problem then mention of algorithms such as Linear Regression or Decision Trees should be made.
Independent Projects, Hackathons, and Publications
Some Data Scientists also partake in independent projects and work on unique projects that expand their knowledge and capabilities. These projects must be mentioned on the resume. In addition to these results of the hackathons should be provided especially of those which are related to the job description and where the result is also high. Lastly, professionals who have some publications such as research papers or books should mention their details in their resume.
Provide Alternative Personal Information
If possible, provide alternative contact information such as an additional mobile number. This can be useful in the case of the employer failing to contact you on your primary contact number. Also, personal information such as residential address should not be provided in great detail. Information such as the locality, city, and state should be more than enough.
Give information (if have) regarding the references. This can provide credibility to your profile. The typical references can be of past employers, professors (if related to the data science or STEM field), and of the professionals working in the company that you are applying at.
Use Important Keywords In The Intro Section
Resumes are often shortlisted by HRs using the Control+F option and looking for job description related keywords or resume screening algorithms that perform text mining and shortlist the relevant resumes. This is where providing important keywords becomes extremely necessary. Terms related to machine learning, deep learning that include the name of languages, packages, algorithms, methodologies such as k-fold cross-validation, etc. must be provided and should also be made bold so that it becomes easy to read.
Provide Measurable Results and Achievements
One thing that should be present in most of the sections, be it certification, academic qualification, or work experience is the constant mention of the achievement. These achievements should not be just mere words but should get into the detail that the employer can comprehend and quantify. The score achieved in the certification and academic courses should be mentioned clearly. Similarly, the achievements made during professional work should be made in a quantitative manner. For example, if your work helped in reducing the losses then the decrease of this loss in terms of percentage should be made.
Avoid Providing Irrelevant Information
There can be information that may be important to you, it may showcase some form of achievement, or it may be important to come to another job but may not be significant for the job you are applying. Such information must be avoided as adding such information will not provide any benefit and will only result in expanding the length of the resume. For example, having information regarding some projects done in marketing may not be useful when applying for a job where the main focus is on natural language processing for topic mining.
Data Scientist Resume Sample
A Data Scientist resume sample can help you in having some idea for creating your own data science resume. In this sample, a typical data science cv is used where all the important topics have been covered. This data science resume is mainly for those who have some work experience.
Special Tips for Entry Level Data Scientist Resume
Data Scientist fresher resume is one of the difficult data science cv to write. The time when the resume plays the most crucial role in getting a candidate considered for a job is when the candidate is a fresher i.e. has no past job experience and here writing an entry-level data scientist resume is important. This is where a lot of work should be put into the creation of the resume. While there are a number of ways through which freshers can get a job in the field of data science, here are the few tried and tested tips that can enrich a fresher’s resume and increase the chances of getting placed.
Mention a clear career objective (In Short)
Nothing sends a bad message than applying for a job just to have one. The employers must be aware of the genuine interests and passion you have for the discipline. Therefore, through the resume, this interest must be conveyed. The resume initially should have a section on career goals or objectives that clearly mention what your aim is for the future, how the job you are applying for compliments it, how suitable you are for the job etc. The job profile must seem to match your interests.
Focus on Education Qualification and Related Achievements
In the event of an academic filed being complementary with the field of Data Science, one must enhance and highlight academic achievements. For candidates belonging to Statistics, Mathematics, or Programming related backgrounds, an attempt must be made to showcase how the academic background is relevant and will help you in performing the job. If there are certain events or competitions that you took part in and if that compliments the job description, then this too must be mentioned. For example, if the job description has focused on statistical models and if you have some distinct achievement in the field of statistics and its application then this can be considered as good value addition.
Information About The Completed Certifications
As often the typical traditional academic fields (especially in India) are not of Data Science, candidates often complete specialized Data Science-based certification that gives them exposure to this field. The resume must-have information on all such certifications. In a section related to the certification, you must mention the name, duration, date of completion of the certificate. Along with this other information such as the skills learned through that certification must be mentioned. Again an attempt must be made to make this description of certification relevant to the job description.
Case Studies and Projects
The main hurdle that freshers face is the lack of practical knowledge. This can be showcased by giving details of the numerous case studies and assignments attempted during the completion of the case studies. In the resume, information regarding these case studies should be there which will include the topic of the case studies, the domain the case study was related to, the problem you faced, and how those problems were solved and the name of the specific tools and methodologies applied to solve them. The assignments and case studies that are relevant to the job description should be highlighted.
Want to work on more hands-on projects? Here are the Top 20 (Interesting) Data Science Projects Ideas With Data
Invest Time On Creating a Linkedin and Github profile
To get a good idea about the capabilities and skills of a candidate, the employers often refer to the LinkedIn id. Candidates must spend a good amount of time working on their LinkedIn profile which should have the information related to their complete academic qualification. LinkedIn also gives an option for providing information regarding the certifications. This URL to your LinkedIn profile must be provided in the resume. In addition to this, the case studies and assignment solutions should be uploaded on the Github repository and the URL for the same must be provided on the resume so that the employers can have a first-hand look at your coding and problem-solving skills.
The other major component that solves the problem of having limited work experience among freshers is having some internships. To secure a job of a Data Scientist or related job profile, freshers must serve time as interns where the nature of the job is related to data science which includes working as data analysts, business analysts, data miners, etc. This experience should be mentioned in the resume and again, an attempt should be made to make this experience relevant to the job description.
To immediately inform the employers of your skills, freshers can have a dedicated section in their resume that simply lists out all the tools and algorithms they are aware of thereby smoothening the screening process. When it comes to Data Science the skills can be divided into languages (such as R and Python), tools or software (such as MS Excel, MS Word, MS PowerPoint, SAS, SPSS, MATLAB), and Databases (e.g. SQL, MongoDB).
Freshers can also simply list out all the algorithms that they know. Here all the algorithms and techniques can be listed out (irrespective of the job description as under this section the idea is just to provide the complete information of the acquired skills).
Entry-level Data Scientist Resume Sample
The below data scientist fresher resume can help in guiding those who have no work experience and are trying to get into the field of Data Science. This below sample can be considered as an entry-level data scientist resume as it provides a framework for writing a resume that can help in targeting basic to intermediate level of data science jobs.
Projects for Data Science Resumes
There is always a requirement for data science projects for resume building. Candidates from all backgrounds, freshers, or otherwise must have an impressive list of projects that have taken part in and have completed. Projects can be provided in various forms. The most common way of getting projects is through certifications. People who partake in certification or even academic courses on Data Science are involved in numerous projects. These projects are handed out in the form of case studies and projects. In the resume, the candidates must mention in detail regarding these case studies, the tools that were used, and the packages that were explored.
The candidates must try to showcase their problem-solving skills by mentioning the peculiar problems that they faced and how their problem-solving skills helped in the completion of projects. In case there are fewer projects or there is no project-related or relevant to the job description then one must try to undertake a related project from online resources. The most common way of getting projects is through websites such as Kaggle where data is available related to various domains.
Related: 20 Interesting Data Science Project
The candidates must do research regarding the domain of the applied job and know the common problems faced in that industry. These problems should be tried to solve in these projects. Eventually, the codes, results, analysis, reports of these projects should be provided on the GitHub repository whose link should be provided in the resume.
Resume for Data Scientist is an important component as it allows the aspirant to secure the desired job. A Data Scientist’s resume in India requires a focus on the work experience as well as the academic aspect of a candidate. Writing a resume is as important of a skill as knowing about the various aspects of Data Science. Thus, learning how to write a Data Science resume is important.
The main aim of any resume is to communicate with the employer regarding the eligibility of a candidate for securing a particular job. The resume must be able to present all the relevant information regarding the education and certification along with providing information regarding the practical knowledge gained through work experience, projects, etc. To stand out from all other candidates, candidates must mention specific skills in their resumes such as the solving of specific problems, independent project work, publications that include research papers and books, and even blogs.
Credibility is one of the main aspects that any employer focuses on thus GitHub repositories should be provided that have the codes of the data science projects mentioned in a resume that the employers can easily go through. In addition to the links to well-created LinkedIn and other social media profiles should be provided.
This article aimed to provide the reader with an understanding of various aspects of writing a Data Science resume for working professionals and freshers with little to no experience. If you have any opinions or queries related to this article, feel free to post and help us get more insights as more things can be added to a resume to make it more attractive and relevant to employers.
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