Introduction: Data Scientist Crowned America’s Top Job in 2019
On June 18, 2019, Glassdoor released its annual ranking of the highest-paying jobs in the United States, and data scientist claimed the top spot with a median base salary of $108,000. As businesses across industries—from tech giants like Google to retail leaders like Walmart—raced to harness the power of data, this role emerged as a cornerstone of the digital economy. For international students, who made up 18% of U.S. STEM graduates in 2019, data science offered a golden ticket: high pay, strong demand, and a path to career stability in a competitive job market.
This article, inspired by Mean Value Consulting’s coverage, dives into why data scientist topped Glassdoor’s 2019 list, exploring the role’s appeal, requirements, and opportunities for international students. With 1,974 reads and growing interest, the story of data science in 2019 is a blueprint for aspiring professionals aiming to break into this high-paying field.
Why Data Scientist Ranked First in 2019
Glassdoor’s 2019 report, based on salary data from thousands of U.S. employees, highlighted data scientist as the highest-paying job, surpassing roles like physician ($193,415) and software engineer ($105,563). The median base salary of $108,000—coupled with bonuses often exceeding $20,000—reflected the role’s critical value in a data-driven world. Here’s why data scientist stood out:
Surging Demand
The U.S. Bureau of Labor Statistics projected a 15% growth in data science jobs from 2019 to 2029, far outpacing the national average of 4%. With companies leveraging data for decision-making, data scientists were needed in tech (40% of roles), finance (15%), and healthcare (10%), per LinkedIn’s 2019 Emerging Jobs Report.
High Impact
Data scientists analyze vast datasets to uncover insights, optimize operations, and drive strategy. For example, they helped Netflix save $1 billion annually through recommendation algorithms and enabled Amazon to boost sales by 35% via predictive analytics. This tangible impact justified premium salaries.
Skill Scarcity
In 2019, only 35,000 data scientists were employed in the U.S., against a demand for 150,000, according to IBM. The shortage of professionals with expertise in statistics, programming, and machine learning fueled high pay and job security.
Flexibility and Prestige
Data scientists enjoyed a 4.1/5 job satisfaction rating on Glassdoor, thanks to remote work options, creative problem-solving, and roles at top firms like Apple and Microsoft. The profession’s prestige made it a magnet for ambitious talent, including international students.
Why Data Science Appeals to International Students
International students, numbering over 1 million in the U.S. in 2019 (IIE), were drawn to data science for its financial and professional rewards. With 53% of international students in STEM fields—particularly from India (20%) and China (35%)—the role aligned perfectly with their academic strengths.
Key Benefits
- High Salaries: The $108,000 median salary covered living costs ($12,000/year in cities like Austin) and helped offset international tuition fees averaging $26,290/year for public universities.
- Visa Pathways: Data science’s inclusion in STEM OPT programs allowed F-1 visa holders to work up to 36 months post-graduation, boosting chances for H-1B visas or permanent residency.
- No Experience Barrier: Entry-level roles often required only a degree and technical skills, making it accessible for students with strong academic backgrounds but limited work history.
- Global Demand: Skills in Python, R, and SQL were transferable worldwide, offering flexibility for students returning to countries like India, where data science jobs grew 400% from 2016 to 2019.
In a 2019 job market where 88.6% of international graduates found employment within three years, data science stood out for its high pay and stability, especially during the economic uncertainty of the looming COVID-19 pandemic.
What Does a Data Scientist Do?
Data scientists blend mathematics, programming, and business acumen to turn raw data into actionable insights. In 2019, typical responsibilities included:
- Data Analysis: Using tools like Python and SQL to analyze sales, customer behavior, or operational data, as seen in Walmart’s inventory optimization.
- Machine Learning: Building predictive models, like fraud detection systems for banks or recommendation engines for e-commerce.
- Visualization: Creating dashboards with Tableau or Power BI to present insights to executives, influencing decisions like Target’s $7 billion supply chain overhaul.
- Collaboration: Working with engineers, marketers, and product managers to align data strategies with business goals.
A 2019 Glassdoor review from a Google data scientist noted, “The role is challenging but rewarding—you solve real problems and see your work drive millions in revenue.”
Eligibility and Skills Needed
While no experience was often required for entry-level roles, data science demanded specific skills and qualifications, ideal for international students in STEM programs:
- Education: A bachelor’s or master’s degree in computer science, statistics, mathematics, or related fields. In 2019, 60% of data scientists held advanced degrees, per LinkedIn.
- Technical Skills: Proficiency in Python, R, SQL, and tools like TensorFlow or Hadoop. Knowledge of machine learning and statistical modeling was a plus.
- Soft Skills: Strong communication to present findings and problem-solving to tackle complex datasets, as emphasized in 80% of job postings.
- Visa Status: International students needed a valid F-1 visa with OPT eligibility for post-graduation work. No prior experience was required for many entry-level roles at firms like IBM or Deloitte.
Bootcamps and online courses, like those from Coursera or edX, helped students bridge skill gaps, with 25% of data scientists in 2019 entering via non-traditional paths.
How to Land a Data Science Job
Breaking into data science in 2019 was competitive but achievable. Here’s how international students could secure a role:
- Build a Strong Portfolio: Showcase projects like predictive models or data visualizations on GitHub. A 2019 survey found 70% of hiring managers valued portfolios over resumes.
- Leverage Online Learning: Complete courses like Andrew Ng’s Machine Learning on Coursera or Stanford Online’s Data Science certificate to gain skills.
- Network: Connect with data scientists on LinkedIn or attend job fairs like Grace Hopper Celebration, which drew 25,000 attendees in 2019.
- Apply Strategically: Use Glassdoor or Indeed to find entry-level roles at companies like Accenture or startups like Datadog. Tailor resumes to highlight Python or SQL skills.
- Prepare for Interviews: Practice coding challenges on LeetCode and behavioral questions like “How would you explain a model to a non-technical stakeholder?” Interviewers prioritized structured problem-solving, per 85% of Glassdoor reviews.
Application Tip: Highlight academic projects, like analyzing university datasets, to demonstrate practical skills, even without work experience.
Challenges for International Students
Despite its appeal, data science posed challenges:
- Visa Restrictions: F-1 students were limited to 20 hours/week of on-campus work during terms, requiring careful compliance to maintain status.
- Competition: With 150,000 open roles and only 35,000 data scientists, competition was fierce, especially at top firms like Amazon.
- Skill Gaps: Some students lacked advanced machine learning knowledge, requiring self-study or bootcamps costing $10,000–$15,000.
- Cultural Barriers: Explaining technical concepts in English or navigating U.S. workplace norms was challenging for 30% of international students, per a 2019 IIE survey.
Solutions included joining university data science clubs, seeking mentorship from professors, and using free resources like Kaggle for practice.
Real Stories: Success in Data Science
The Glassdoor ranking inspired action. Priya, an Indian master’s student at NYU, landed a data analyst role at IBM after completing a Kaggle project. “The $108,000 salary was life-changing, and OPT gave me time to transition to H-1B,” she shared on LinkedIn. A Reddit thread from June 2019 featured a Chinese student at UT Austin who secured a role at Deloitte, noting, “My statistics coursework and a Python certificate were enough to get in.” These stories highlight data science’s accessibility for motivated students.
Why 2019 Was a Pivotal Year
In 2019, the U.S. job market was robust, with 3.5% unemployment and tech driving 20% of job growth (BLS). Data science’s top ranking reflected the digital transformation sweeping industries, with 90% of companies investing in AI and analytics, per Forbes. For international students, the role offered a path to financial security and visa stability amid looming immigration policy changes, like ICE’s 2020 unlawful presence rule. The $108,000 salary and STEM OPT eligibility made data science a beacon in a competitive landscape.
Conclusion: Your Path to a Data Science Career
Glassdoor’s 2019 ranking of data scientist as the highest-paying U.S. job, with a $108,000 median salary, underscored its value in a data-driven world. For international students, the role offered high pay, visa flexibility, and global opportunities, making it a top choice in a year of economic strength. By building technical skills, leveraging academic resources, and navigating visa rules, students could break into this booming field, even without experience.
Though the 2019 job market has evolved, data science remains a top career in 2023. Visit www.glassdoor.com or www.indeed.com to explore current openings, and start your journey with platforms like Kaggle or Coursera. For international students with ambition and a knack for numbers, data science is a path to a rewarding future.
