Data Science Salary Guide 2026: Entry Level to Senior

Data science remains one of the most lucrative career paths in 2026, with salaries continuing to rise across all experience levels. This comprehensive guide breaks down compensation expectations for entry-level, mid-level, and senior data scientists across different regions, industries, and specializations.

Executive Summary: 2026 Salary Trends

The data science job market has evolved significantly in 2026. While AI tools have automated some routine tasks, they've also increased the demand for senior professionals who can leverage these tools strategically. This has created a widening salary gap between entry-level and senior positions, with specialists in AI, machine learning engineering, and MLOps commanding the highest premiums.

Entry-Level Data Science Salaries (0-2 years)

Entry-level data scientists typically have 0-2 years of experience, recent degrees, or have completed bootcamps/certificates.

United States

• Junior Data Scientist: $80,000 - $95,000
• Entry-Level ML Engineer: $85,000 - $105,000
• Data Analyst (entry): $65,000 - $80,000
• Recent Graduate (Master's): $85,000 - $100,000

United Kingdom

• Junior Data Scientist: £35,000 - £45,000
• Entry-Level ML Engineer: £40,000 - £50,000
• Data Analyst (entry): £28,000 - £35,000

Europe (Germany, France, Netherlands)

• Junior Data Scientist: €45,000 - €55,000
• Entry-Level ML Engineer: €50,000 - €60,000
• Data Analyst (entry): €38,000 - €48,000

Remote/Global

• Remote Junior Roles: $70,000 - $85,000
• US-based remote: $75,000 - $90,000
• EU-based remote: €45,000 - €55,000

What Affects Entry-Level Salaries?

• Education: Master's degree holders typically start $10,000-$15,000 higher
• Location: SF/Bay Area commands 20-30% premium, NYC 15-25%
• Portfolio: Strong GitHub/Kaggle presence can increase offers by $10,000+
• Industry: Finance and pharma pay 15-25% more than startups
• Company Size: Big tech (FAANG) pays $95,000-$110,000 for entry-level

Mid-Level Data Science Salaries (2-5 years)

Mid-level professionals have 2-5 years of experience, typically lead projects, and specialize in specific domains.

United States

• Data Scientist: $110,000 - $150,000
• ML Engineer: $125,000 - $165,000
• Senior Data Analyst: $90,000 - $115,000
• Data Scientist (Finance): $140,000 - $175,000
• ML Engineer (Big Tech): $160,000 - $200,000

United Kingdom

• Data Scientist: £55,000 - £75,000
• ML Engineer: £65,000 - £85,000
• Senior Data Analyst: £45,000 - £60,000

Europe

• Data Scientist: €65,000 - €85,000
• ML Engineer: €75,000 - €95,000
• Senior Data Analyst: €55,000 - €70,000

Key Mid-Level Salary Factors

• Specialization: ML engineers earn 15-20% more than general data scientists
• Industry Premium:
  • Finance/Quant: +25% to base
  • Healthcare/Pharma: +15% to base
  • Tech/Software: +10% to base
• Company Stage:
  • Public/Big Tech: +20-30%
  • Series C+ Startup: +10-15%
  • Early-stage: Base to -10% (equity upside)
• Skills Premium:
  • Deep Learning: +$15,000-$25,000
  • MLOps/Deployment: +$10,000-$20,000
  • Cloud expertise (AWS/GCP/Azure): +$10,000

Senior Data Science Salaries (5+ years)

Senior professionals lead teams, architect solutions, and drive strategy. Salaries vary dramatically based on scope and impact.

United States

• Senior Data Scientist: $150,000 - $200,000
• Staff ML Engineer: $180,000 - $250,000
• Principal Data Scientist: $200,000 - $300,000
• Head of Data Science: $250,000 - $400,000+
• Director of Data Science: $300,000 - $500,000+

United Kingdom

• Senior Data Scientist: £80,000 - £110,000
• Staff ML Engineer: £95,000 - £130,000
• Principal Data Scientist: £110,000 - £150,000
• Head of Data Science: £140,000 - £200,000+

Europe

• Senior Data Scientist: €95,000 - €125,000
• Staff ML Engineer: €110,000 - €145,000
• Principal Data Scientist: €130,000 - €170,000
• Head of Data Science: €160,000 - €220,000+

Total Compensation Breakdown (Senior Level)

At senior levels, base salary is only part of the picture. Here's a typical total compensation package for a Senior Data Scientist at a major tech company in the US:

• Base Salary: $180,000
• Bonus: 15-25% ($27,000 - $45,000)
• Stock/Equity: $80,000 - $150,000 (annualized)
• Benefits: $20,000+ (health, 401k, etc.)
• Total: $307,000 - $395,000+

Industry-Specific Salary Data

Different industries offer varying compensation structures based on data maturity and business impact.

Technology/Software

• Entry: $80,000 - $95,000
• Mid: $120,000 - $160,000
• Senior: $170,000 - $250,000
• Perks: Heavy equity, remote flexibility

Finance/FinTech

• Entry: $85,000 - $105,000
• Mid: $140,000 - $180,000
• Senior: $200,000 - $300,000
• Perks: Bonuses up to 50%, profit sharing

Healthcare/Pharma

• Entry: $75,000 - $90,000
• Mid: $110,000 - $145,000
• Senior: $160,000 - $220,000
• Perks: Stability, impact, good benefits

E-commerce/Retail

• Entry: $75,000 - $90,000
• Mid: $105,000 - $140,000
• Senior: $150,000 - $200,000
• Perks: Product visibility, bonuses

Consulting

• Entry: $80,000 - $95,000
• Mid: $120,000 - $160,000
• Senior: $180,000 - $250,000
• Perks: Varied exposure, travel, bonuses

Specialization Premium (2026)

Specialized skills continue to command significant premiums in 2026:

Specialization	Salary Premium	In-Demand Skills
ML Engineering	+20-30%	MLOps, deployment, TensorFlow/PyTorch
LLMs/GenAI	+30-40%	LangChain, RAG, prompt engineering
Computer Vision	+15-25%	OpenCV, YOLO, medical imaging
NLP	+20-30%	Transformers, spaCy, sentiment analysis
MLOps	+25-35%	MLflow, Kubeflow, model monitoring
Data Engineering	+10-20%	Spark, Airflow, cloud platforms

Regional Variations Within Countries

United States

• San Francisco/Bay Area: +30% to national average
• New York City: +20% to national average
• Seattle: +15% to national average
• Boston: +10% to national average
• Austin, Denver: National average to +5%
• Remote (US-based): -5% to +5% depending on company

United Kingdom

• London: +25-30% to national average
• Manchester: +5-10%
• Edinburgh: +5-10%
• Birmingham: National average
• Remote (UK): -5% to national average

Continental Europe

• Switzerland (Zurich, Geneva): +40-50% to EU average
• Germany (Munich, Berlin): +10-15% to EU average
• Netherlands (Amsterdam): +15-20% to EU average
• France (Paris): +5-10% to EU average
• Spain, Italy: -10-15% to EU average

Salary Negotiation Strategies

Research Your Market Value

• Use multiple sources (Glassdoor, Levels.fyi, Reddit)
• Consider total compensation, not just base
• Account for cost of living differences
• Factor in company size and stage

Timing Your Negotiation

• Best times: Performance reviews, promotion discussions, after major wins
• Leverage points: Counteroffers, other opportunities, market rate data
• Avoid: First 3 months (prove yourself first), during layoffs

Negotiation Tactics

• Anchor high: Start 15-20% above your target
• Total comp focus: Negotiate base + bonus + equity together
• Non-monetary: Remote work, flexible hours, learning budget
• Silence is power: Let them respond, don't fill the gap

2026 Salary Projections

Based on current trends, here are projections for late 2026:

• General Data Science: +5-8% from 2025
• ML Engineering: +8-12% from 2025
• LLM/GenAI Specialists: +15-25% from 2025
• Entry-level: Slower growth (3-5%) due to AI automation
• Senior-level: Faster growth (10-15%) due to leadership demand

Total Compensation Calculator

When evaluating offers, calculate total annual compensation:

Base Salary: $150,000
Annual Bonus: $22,500 (15%)
Equity (annualized): $40,000
401k Match: $7,500
Health Benefits: $8,000
Learning Budget: $5,000
Remote Work Stipend: $3,000
---
Total: $236,000

Remember: Equity is pre-tax and illiquid. Consider it a bonus, not guaranteed income.

Conclusion

Data science salaries in 2026 remain strong, particularly for specialists and senior professionals. The key to maximizing your earning potential is:

• Continuous learning in high-demand areas (MLOps, LLMs, deployment)
• Strategic career moves every 2-3 years for 15-30% raises
• Building specialized expertise that commands premium pay
• Negotiating total compensation, not just base salary
• Geographic flexibility if remote options are available The data science field continues to evolve, but skilled professionals who can leverage AI tools strategically—rather than being replaced by them—will continue to see strong salary growth and abundant opportunities. Ready to explore data science opportunities? Browse our job board to see current salary ranges and open positions across all experience levels.