India’s tech industry has witnessed a surge in salary expectations over the past few years, particularly in fields such as data science and artificial intelligence. With startups and product-based companies offering attractive compensation packages, mid-level professionals are increasingly setting ambitious benchmarks for themselves. While some of these expectations are rooted in market realities, others appear to be influenced by social media hype and anecdotal success stories, creating a complex landscape for both job seekers and employers.
Rising Salary Demands
A recent discussion on Reddit highlighted that data scientists with around five years of experience are increasingly asking for 50 LPA or more during interviews. Shared in a Reddit post, according to a person working in a product-based MNC, most of these candidates come from service or consulting firms. Their experience typically involves standard analytics work or basic Gen AI projects, without standout achievements or experience at top-tier product companies.
Despite this, these professionals approach interviews expecting substantial pay, assuming such compensation is common. The poster questioned whether the current market can support these demands or if perceptions are skewed by exaggerated success stories online.
Perspective on Skills and Justified Expectations
Commenters noted that high pay is justified only for exceptional skills. One user explained that companies value candidates with a mix of hard and soft skills, including deep technical understanding beyond standard libraries, domain expertise, clear communication, and problem-solving abilities. Candidates with unique contributions, innovative implementations, or published research are more likely to command top-tier salaries.
Another commenter emphasized that resumes from smaller companies can also be compelling, provided the candidate demonstrates tangible impact. Social media often exaggerates compensation trends, so the reality for most mid-level professionals is usually lower than the inflated figures circulating online.
Benchmarking Reality Versus Perception
Several voices in the discussion stressed the importance of self-assessment. Simply replicating AI models or following research papers does not justify high pay unless accompanied by measurable outcomes. Salary expectations are also influenced by current compensation and competing offers, and companies will only match high demands if the candidate brings significant value.
Rising Salary Demands
A recent discussion on Reddit highlighted that data scientists with around five years of experience are increasingly asking for 50 LPA or more during interviews. Shared in a Reddit post, according to a person working in a product-based MNC, most of these candidates come from service or consulting firms. Their experience typically involves standard analytics work or basic Gen AI projects, without standout achievements or experience at top-tier product companies.
Despite this, these professionals approach interviews expecting substantial pay, assuming such compensation is common. The poster questioned whether the current market can support these demands or if perceptions are skewed by exaggerated success stories online.
Perspective on Skills and Justified Expectations
Commenters noted that high pay is justified only for exceptional skills. One user explained that companies value candidates with a mix of hard and soft skills, including deep technical understanding beyond standard libraries, domain expertise, clear communication, and problem-solving abilities. Candidates with unique contributions, innovative implementations, or published research are more likely to command top-tier salaries.
Another commenter emphasized that resumes from smaller companies can also be compelling, provided the candidate demonstrates tangible impact. Social media often exaggerates compensation trends, so the reality for most mid-level professionals is usually lower than the inflated figures circulating online.
Benchmarking Reality Versus Perception
Several voices in the discussion stressed the importance of self-assessment. Simply replicating AI models or following research papers does not justify high pay unless accompanied by measurable outcomes. Salary expectations are also influenced by current compensation and competing offers, and companies will only match high demands if the candidate brings significant value.
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