How do you stop data science salary discrimination?

Data science is one of the most lucrative and in-demand fields in the world, but it also comes with its own challenges and pitfalls. One of them is salary discrimination, which can affect your career prospects, motivation, and self-worth. Salary discrimination can occur when data scientists are paid differently based on factors such as gender, race, age, location, education, or experience, rather than on their skills, performance, or value. How do you stop data science salary discrimination and ensure that you get paid fairly and equitably? Here are some tips and strategies to help you.

1 Know your worth

The first step to stop data science salary discrimination is to know your worth as a data scientist. This means researching the market rates for your role, level, industry, and location, and benchmarking your skills and achievements against them. You can use online tools, such as Glassdoor, PayScale, or Hired, to find salary data and insights for data science jobs. You can also network with other data scientists, mentors, or recruiters, and ask them for feedback and advice on your salary expectations and negotiations.

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Muhammad Imran Zaman

Lead Machine Learning Engineer @ DOCUFY GmbH I Kaggle Grandmaster I Generative AI Expert I LLM Expert I Helping Data Science community to polish their skills
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Essential advice for combating data science salary disparities. Research market rates, considering role, level, industry, and location, then align your skills and accomplishments accordingly. Leverage tools like Glassdoor, PayScale, or Hired for salary insights. Tap into networks of fellow data scientists, mentors, and recruiters for feedback and negotiation support. By advocating for your true value, you not only empower yourself but contribute to fairer compensation standards across the data science landscape. Remember, informed negotiation is a stepping stone toward equitable remuneration and industry-wide change.

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2 Negotiate confidently

The second step to stop data science salary discrimination is to negotiate confidently and assertively for your desired salary. This means preparing a strong case for why you deserve the salary you are asking for, based on your skills, experience, impact, and value. You should also anticipate and overcome potential objections, such as budget constraints, market conditions, or internal policies. You should also avoid revealing your current or past salary, as this can limit your bargaining power and anchor the employer's offer. Instead, focus on your target salary range and the value you can bring to the role.

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Adam Brown Sr.

Consultant | Life Science Professional
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Could you provide candidates with a clear salary range during the hiring process? This allows candidates to make informed decisions and negotiate based on their qualifications rather than potentially biased negotiation skills.

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Mallory Rogers, MBA

Data & Analytics Leader | Top 20 Rising Star in Data & Analytics ’24 | Transforming Clinical Trial Operations through Technology Implementation + Optimization | Strategic Change Management + Education
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If possible, avoid being the first party to state a number. If you must, then aim high, and add a caveat. An example I’ve used before: “I’m looking for <insert amount> but that number is dependent on the entire compensation package.” This phrase opens you up to be able to adjust higher OR lower at a later time if the benefits, bonus, or PTO are less generous than you would prefer.

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3 Document your achievements

The third step to stop data science salary discrimination is to document your achievements and contributions as a data scientist. This means keeping track of your projects, tasks, outcomes, and feedback, and highlighting them in your resume, portfolio, and performance reviews. You should also quantify your achievements using metrics, such as revenue, cost, efficiency, accuracy, or customer satisfaction, and showcase your impact on the business goals and objectives. By documenting your achievements, you can demonstrate your worth and justify your salary demands.

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4 Seek feedback and guidance

The fourth step to stop data science salary discrimination is to seek feedback and guidance from your manager, peers, or mentors. This means asking for regular and constructive feedback on your work, performance, and career development, and using it to improve your skills, knowledge, and confidence. You should also seek guidance on how to advance your career, such as taking on more responsibilities, learning new technologies, or pursuing certifications or degrees. By seeking feedback and guidance, you can show your initiative and ambition, and align your career goals with the expectations and opportunities in your organization.

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5 Advocate for yourself and others

The fifth step to stop data science salary discrimination is to advocate for yourself and others who may face similar challenges. This means speaking up for your rights and interests, and raising any issues or concerns that you may have about your salary or working conditions. You should also support and mentor other data scientists who may face salary discrimination, and share your experiences, insights, and resources with them. You should also join or create communities, networks, or groups that promote diversity, inclusion, and equity in data science, and participate in their events, activities, or campaigns.

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6 Explore other options

The sixth and final step to stop data science salary discrimination is to explore other options if you are not satisfied with your current situation. This means looking for other data science jobs or roles that may offer better pay, benefits, or opportunities, and applying for them with confidence and preparation. You should also consider other ways to increase your income, such as freelancing, consulting, teaching, or creating content. You should also keep learning and updating your skills, and building your personal brand and network, to enhance your employability and marketability in data science.

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Joel Atkins

Data Science Leader | Actuary (FCAS) | Drawing Actionable Insights from Data
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I find this step a little ironic. One of the main causes of internal inequity in salaries is when one candidate or employee has competing offers and a company feels the need to match those offers. This might be a signal that the candidate is worth more, but it may also be rewarding those candidates who shop more.

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7 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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How do you stop data science salary discrimination?

1

2

3

4

5

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7

1 Know your worth

2 Negotiate confidently

3 Document your achievements

4 Seek feedback and guidance

5 Advocate for yourself and others

6 Explore other options

7 Here’s what else to consider

Data Science

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How do you stop data science salary discrimination?

1

2

3

4

5

6

7

1 Know your worth

2 Negotiate confidently

3 Document your achievements

4 Seek feedback and guidance

5 Advocate for yourself and others

6 Explore other options

7 Here’s what else to consider

Data Science

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