How do I tailor my cv to tell a better history?
- I am 33, I just finish my doctorate, I am not fully committed to the academic area. How should I tailor my cv for the market (data-engineering or R&D engineering)?
- I feel like I have many skills (google cloud platform, python, digital transformation project coordinator), but the market is searching for specific things, what should I do about it?
- I am older, I have experience in areas that can be related but not so directly, how to close the gap between skills/experiences and my cv?
9 answers
Rajesh Kumar’s Answer
Focus on Relevant Skills and Experiences: Highlight the skills and experiences that directly align with the roles you are targeting, such as data engineering or R&D engineering. Emphasize your proficiency in relevant technologies like Google Cloud Platform, Python, and any other tools or languages commonly used in these fields.
Highlight Achievements and Impact: Showcase your accomplishments and the impact you made in previous roles, even if they are not directly related to the positions you are targeting. Focus on transferable skills and experiences that demonstrate your ability to solve problems, work in teams, and deliver results.
Tailor Your CV for Each Application: Customize your CV for each specific job application to highlight the most relevant skills and experiences sought by the employer. Carefully review the job description and incorporate keywords and phrases from it to demonstrate your fit for the role.
Show Continuous Learning: Highlight any additional training, certifications, or courses you have completed, especially those that are relevant to the positions you are applying for. This demonstrates your commitment to ongoing learning and staying updated with industry trends.
Address the Experience Gap: If you have experience in areas that are not directly related to the roles you are pursuing, find ways to bridge the gap. Emphasize transferable skills and experiences that can be applicable to the new field. Focus on how your diverse background brings a unique perspective and a broader skill set to the table.
Networking and Referrals: Leverage your network and seek referrals from professionals already working in the industry. Personal connections can help you overcome potential biases related to age or experience gaps and provide valuable insights and opportunities.
Consider Internships or Volunteer Work: If necessary, consider internships or volunteer work in the field you are targeting. This can provide you with hands-on experience and help demonstrate your commitment and willingness to learn and contribute.
Remember, your CV serves as a marketing tool to showcase your strengths and fit for the role. By tailoring it to highlight relevant skills, experiences, and achievements, you can present yourself as a strong candidate and increase your chances of landing a job in the data engineering or R&D engineering fields.
abdjabbar’s Answer
Mikun’s Answer
Fresh out of college myself, I completely understand the whirlwind that is the current job market. Now, more than ever, having a standout resume is crucial. I'd strongly suggest customizing your resume for each job application. Recruiters use an Applicant Tracking System (ATS) to sift through resumes, and if yours doesn't contain the right keywords or doesn't tell a compelling story, it may not even reach the hiring manager.
So, my advice is to keep a flexible version of your resume on hand, one that you can tweak as needed. Pull out key words and skills from the job description, list your responsibilities in bullet points, quantify your achievements with relevant numbers, and steer clear of fancy fonts, templates or images. This will ensure that the recruiter and their ATS stay focused on your potential for the job, significantly improving your chances.
However, relying solely on online applications won't cut it. You need to go the extra mile, do things that set you apart from the crowd. This could mean attending job fairs, networking events, asking your friends and family for referrals, and so on. Show them that you're willing to step out of your comfort zone, and that you're more motivated than the rest.
Reena’s Answer
Congratulations on finishing your doctorate. That's a huge accomplishment!
Here's how you can tailor your CV for those roles:
Shine a light on your transferable skills: Think about all that research you did – that translates to top-notch analytical and problem-solving skills, exactly what engineers need! Did you use any data analysis tools or techniques during your research? Highlight those (especially Python or anything related to data visualization) – they're gold in this field. And don't forget that project you coordinated – that showcases your ability to manage complex tasks and collaborate with a team, which is crucial for any engineering project.
Tailor your story: Going for data engineering? Put those Python and Google Cloud Platform (GCP) skills front and center. Show how you used them in your research, even if it wasn't exactly data-focused. For example, "Used Python to analyze and visualize research data, resulting in a published paper on [topic]." Similarly, for R&D engineering, emphasize your research experience – it demonstrates your ability to innovate, solve problems, and potentially even prototype new technologies.
Bridge the experience gap: Many companies use applicant tracking systems (ATS) that scan for keywords. Read job descriptions in your target field and sprinkle those keywords throughout your CV. Also, when describing your experience, use numbers and metrics to showcase the impact of your research or project coordination. For example, mention the size of the datasets you analyzed or the number of team members you managed.
By focusing on these transferable skills, tailoring your CV, and bridging the experience gap, you'll be well on your way to landing a data or R&D engineering role!
Check this out for inspiration:
https://www.tealhq.com/resume-examples/data-engineer
Jeff’s Answer
Congratulations on earning your doctorate!
You have already received a great deal of really good information and suggestions. so I won't rehash. But I want to add a few suggestions. First, generally, a CV is a complete overview of all of one's experiences and expertise. My CV is over ten pages from a very long, diverse career. Outside of academia, most hiring managers do not want to see that level of detail. When I was hiring, I would receive a huge stack of resumes every Monday morning. My initial goal was to wade through and eliminate as many as could otherwise I would have to spend days weeding through them all. If I received a full CV with many pages, I glanced at the first page and then usually tossed it in the trash. I suggest you keep your resume to under two full pages. Most managers will only scan page 1 so that has to contain everything important. Second, be very careful about spelling. Typos showed me that the candidate did not care enough to proofread their resume. Third, use action verbs and specifics whenever possible. It catches attention. If you figured out a way to spped upa process, tell the reader that you revolutionized the process by shaving ten seconds off the overall time! Anything you can quantify!
Best of luck!
Melissa’s Answer
Good advice above, and yes, congratulations!
This was helpful to a friend who was in a similar situation - if you want to tailor a CV for non-academic career prospects: https://www.imperial.ac.uk/media/imperial-college/administration-and-support-services/careers-service/public/the-application-process/How-to-write-a-CV-for-roles-outside-academia.pdf
Hope it's helpful to you too.
All the best,
M
James Constantine Frangos
James Constantine’s Answer
Crafting a CV for Data Engineering or R&D Engineering Positions
As you pivot towards data engineering or R&D engineering roles after your doctorate, without fully immersing in academia, there are several tactics to highlight your abilities and experiences effectively:
1. Spotlight Key Skills:
Showcase your expertise in Google Cloud Platform, Python, and your role as a digital transformation project coordinator. These technical skills are in high demand in the tech industry, particularly in data engineering and R&D roles.
2. Adapt Your CV for Each Job:
Make your CV unique for each job application by matching your abilities and experiences with the job's specific needs. Incorporate keywords from the job posting to illustrate how your background aligns with the role's requirements.
3. Highlight Transferable Skills:
Even if your past experiences don't directly relate to data engineering or R&D engineering, underscore transferable skills like problem-solving, analytical thinking, project management, and research skills that are beneficial in these areas.
4. Craft a Professional Summary:
Create an engaging professional summary at the start of your CV that concisely conveys your career aspirations, relevant skills, and what you can offer potential employers in the data engineering or R&D engineering sectors.
5. Detail Your Education:
Since you've recently earned a doctorate, accentuate this accomplishment in your CV's education section. Feature any research projects, publications, or academic achievements that show your expertise and dedication to continuous learning.
6. Describe Your Experience:
When outlining your work experience, concentrate on achievements rather than just job responsibilities. Quantify your achievements where possible and illustrate how you've utilized your skills to deliver results in past roles.
Bridging the Skills/Experience Gap in Your CV: To address any potential gap between your current skills/experiences and the necessities of data engineering or R&D engineering roles:
Think about obtaining additional certifications or training in relevant fields like data analysis, machine learning, or software development.
Explore networking opportunities in the industry to connect with professionals who can offer advice on transitioning into these sectors.
Use any relevant projects or side jobs you've done outside academia to show practical experience in data-related tasks.
By smartly adapting your CV to spotlight your strengths, aligning with job requirements, highlighting transferable skills, emphasizing educational achievements, focusing on past accomplishments, and taking proactive steps to improve your skills, you can effectively position yourself for success in landing data engineering or R&D engineering roles.
Top 3 Reliable Sources Used:
Harvard Business Review: Offers advice on career growth strategies and tips for moving into new sectors.
LinkedIn Learning: Provides online courses and resources on technical skills like Python programming and Google Cloud Platform, which are pertinent for data engineering roles.
Glassdoor: A platform to research job descriptions for data engineering and R&D engineering positions to effectively adapt your CV based on industry standards.
Blessings,
JC.
Aoife’s Answer
Congratulations on the remarkable achievement of completing your doctorate at the age of 33! Remember, it's never too late to change your path. It's truly thrilling to hear about your interest in venturing into data-engineering or R&D engineering. You're absolutely right, you possess a wealth of skills that extend beyond the academic realm, each contributing to a broader comprehension of the diverse demands in the professional world. Make sure to highlight your strengths and never underestimate the potential of the systems you're already familiar with. If a company is genuinely interested in you, they'll likely invest in your training for any specific skill or ability they deem necessary. Remember, age is just a number and doesn't define your capabilities or potential.
Wishing you the best of luck,
Aoife
Aman’s Answer
Tailoring your CV to reflect a coherent and marketable narrative is absolutely essential, especially given your diverse background and newly acquired doctorate. Given your interest in data engineering and R&D engineering, start by focusing on the skills that directly align with those fields. For instance, highlight your proficiency with Google Cloud Platform and Python by showcasing specific projects where you utilized these technologies. Instead of just listing them, elaborate on how you used Python to automate processes or analyze data sets in your previous roles,
If you've coordinated digital transformation projects, detail your role in these initiatives. Were you responsible for implementing new database solutions or improving data pipelines? Make sure to quantify your achievements wherever possible. For example, mention how you improved efficiency by X% through a specific project.
Since the market often seeks specific skills, consider completing targeted online courses or certifications related to data engineering. Platforms like Coursera or LinkedIn Learning offer courses that can fill in any gaps and bolster your résumé with recognizable endorsements. Also, when you write your CV, use keywords from job descriptions of positions you’re interested in. This helps to ensure that applicant tracking systems will flag your resume for consideration.
Finally, tailor your CV’s summary section to reflect your unique blend of skills and your interest in transitioning to these fields. A personal statement that highlights your interdisciplinary approach and how your academic insights bring value to engineering roles can make a compelling case for potential employers.
Best of luck!