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What do you do if you can't negotiate a higher salary in data visualization?

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Data visualization is a valuable skill that can help you communicate insights, tell stories, and persuade audiences with data. But what if you feel like you're not getting paid enough for your work, and you can't negotiate a higher salary or a raise with your employer? In this article, we'll explore some strategies that can help you cope with this situation and improve your career prospects in data visualization.

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Matthew Oladiran

Data Scientist | Data Analyst | Transforming Complex Data into Clear, Actionable Insights for Impactful Decision-Making

1 Assess your value

The first step is to evaluate your current value as a data visualization professional. How do you compare to others in your field, industry, and location? What are the market rates and trends for data visualization jobs? How do you measure your impact and performance? You can use online tools, surveys, and networks to gather this information and benchmark yourself. This will help you understand your strengths, weaknesses, and areas of improvement.

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Matthew Oladiran

Data Scientist | Data Analyst | Transforming Complex Data into Clear, Actionable Insights for Impactful Decision-Making
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One thing I have found helpful is to create a list of KPIs or checklists to score yourself based on what the industry requires. You might be very good but you have not really applied yourself to allow recruiters consider offering you what you desire. The checklist helps you understand what you have not been doing.

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Will Chinn

Head of Recruitment & Global Talent Solutions
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You need to work out the blockers to why you can’t get a raise. In some areas a data vis / bi isn’t seen a generating direct value for the business so negotiation for a salary is tough. Work out who the decision makers are, what motivates them and then try show the impact you have on the business, the positive value you add. If it comes to if you can also leverage the cost of finding a replacement, they will almost always need a higher salary and a recruitment fee. Hiring new people is costly and time consuming.

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Anastasia Gisina

Product Analytics Lead @ Dostavista | AB-test, SQL, Python, BI, ML | Transforming Data into Strategic Product Decisions
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First of all, I recommend evaluating the relevance of your skills. To do this, evaluate the availability of certain skills: look at the profiles of other specialists on your LinkedIn profile who work in the company of your dreams. You can even write to them and ask them your questions. Also, check how well your salary matches the market. You can use local salary surveys for this, or a global service, such as Glassdoor.

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2 Improve your skills

The next step is to invest in your professional development and upgrade your skills. Data visualization is a dynamic and evolving field that requires constant learning and adaptation. You can take online courses, read books and blogs, watch tutorials and webinars, and join communities and events to learn new techniques, tools, and best practices. You can also work on personal or pro bono projects to showcase your portfolio and demonstrate your capabilities.

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Anastasia Gisina

Product Analytics Lead @ Dostavista | AB-test, SQL, Python, BI, ML | Transforming Data into Strategic Product Decisions
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I recommend defining a specific list of skills that you currently lock. Here are some ideas for improving your skills: 1. Attend a hackathon or other intensive course on the desired skill. Search for a professional community. 2. Make sure to attend interviews where you are asked about knowledge of this skill. Start doing it right away, even if you don't know anything in this field. This way, you will understand the requirements and how much you need this skill. 3. Read articles on Medium, take courses on LinkedIn, and watch videos on YouTube.

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3 Expand your network

Another step is to build and maintain your network of contacts and connections in the data visualization field. Networking can help you discover new opportunities, get referrals and recommendations, and learn from others' experiences and feedback. You can use social media platforms, such as LinkedIn, Twitter, and Medium, to share your work, connect with peers and experts, and participate in discussions and groups. You can also attend meetups, conferences, and workshops to meet new people and exchange ideas.

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4 Seek feedback

A crucial step is to seek feedback from your employer, clients, colleagues, and mentors on your data visualization work. Feedback can help you improve your quality, creativity, and effectiveness of your data visualizations. It can also help you identify your areas of improvement, gaps in your knowledge, and mistakes to avoid. You can ask for feedback regularly, formally or informally, and use it to set goals and action plans for your growth.

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5 Explore alternatives

The final step is to explore alternative options for your career path in data visualization. If you can't negotiate a higher salary or a raise with your current employer, you may want to look for other employers or clients who can offer you better compensation and benefits. You can use job boards, platforms, and agencies to find and apply for data visualization jobs that match your skills, interests, and expectations. You can also consider freelancing, consulting, or starting your own business in data visualization if you have the skills, experience, and network to do so.

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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What do you do if you can't negotiate a higher salary in data visualization?

1

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3

4

5

6

1 Assess your value

2 Improve your skills

3 Expand your network

4 Seek feedback

5 Explore alternatives

6 Here’s what else to consider

Data Visualization

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What do you do if you can't negotiate a higher salary in data visualization?

1

2

3

4

5

6

1 Assess your value

2 Improve your skills

3 Expand your network

4 Seek feedback

5 Explore alternatives

6 Here’s what else to consider

Data Visualization

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