Bioinformatics ML Scientist
Impact: Drug discovery and disease understanding through expert bioinformatics ML research
Apply machine learning and AI techniques to biological data including genomics, proteomics, and clinical data to advance drug discovery, disease understanding, and personalised medicine. Build ML models for biological sequence analysis, protein structure prediction, and clinical outcome prediction.
What the day looks like
- People interaction
- Moderate
- Team vs solo
- 60% Team / 40% Solo
- Client facing
- Sometimes
- Impact visibility
- Moderate
- Travel
- 5 to 10% for conferences and laboratory visits
- Schedule flexibility
- Flexible
- Remote work
- Hybrid
- Typical work hours
- 45 to 60 hours/week
- Stress level
- Low
At a glance
- Median salary
- $220,000
- Entry-level
- $120,000 - $160,000
- Senior
- $380,000+
- Growth by 2033
- 25% (faster than average)
- Demand
- Growing Fast
- Freelance potential
- Low
- Salary growth potential
- High - 65 to 80% growth from entry to senior
- Typical student debt
- Low
Skills you'll use
Hard skills
- 55
Soft skills
- 45
Technical complexity: Moderate
How to get there
- Minimum education
- PhD
- Licensing
- No
- Years to mid-career
- 3 to 5 years
- Years to senior
- 7 to 10 years
- Career switching
- Hard
Where this career leads
How people arrive here
Where you can go from here
Typical progression
- Bioinformatics Analyst > ML Scientist > Bioinformatics ML Scientist > Senior Bioinformatics ML Scientist > Head of Computational Biology
Future outlook
- Automation probability
- 10% very low risk as bioinformatics ML requires deep expertise
- AI disruption risk
- Very Low
- Demand trend
- Growing Fast
How people feel about it
- Overall satisfaction
- 7/10
- Meaning
- 7/10
- Work-life balance
- 6.5/10
- Prestige
- 7/10
- Social perception
- High