What can you do with a PhD in Mathematics?

1. Finance (Quant, Risk, Data Analytics)

✅ Key Skills to Develop:

• Financial modeling, time series analysis
• Probability, statistics, and stochastic processes
• Machine learning applications in finance
• Python (pandas, NumPy, scikit-learn), R, SQL
• Tools: Bloomberg Terminal, Excel (VBA), Power BI

✅ What to Do:

• Take a Financial Engineering/Quantitative Finance course
• Learn algorithmic trading and practice on platforms like QuantConnect or Kaggle
• Earn certifications like CFA (Chartered Financial Analyst) or FRM (Financial Risk Manager)
• Apply for Quantitative Analyst, Risk Analyst, or Financial Data Scientist roles

🔗 Where to Apply: Investment banks, hedge funds, asset management firms, fintech startups

 Example Role: Quantitative Analyst at Goldman Sachs - Develop statistical models for risk assessment - Implement trading algorithms in Python and R - Analyze financial trends and optimize investment strategies 

2. Tech (Data Science, AI, Software Development)

✅ Key Skills to Develop:

• Machine learning, deep learning, reinforcement learning
• Big data tools: Spark, Hadoop
• Cloud computing: AWS, Azure, Google Cloud
• Python, SQL, R, Git, Tableau, Power BI

✅ What to Do:

• Build AI/ML projects and contribute to GitHub/Kaggle
• Earn Google Data Analytics, TensorFlow Developer, or AWS AI/ML certifications
• Take LeetCode-style coding interviews (since tech roles often require algorithmic problem-solving)
• Apply for Data Scientist, Machine Learning Engineer, AI Researcher, Software Engineer roles

🔗 Where to Apply: Google, Amazon, Microsoft, Tesla, Facebook, IBM, OpenAI, Palantir

 Example Role: Machine Learning Engineer at Google - Build predictive models for user behavior analysis - Work with TensorFlow and PyTorch to develop AI solutions - Optimize deep learning algorithms for large-scale applications 

3. Energy (Oil & Gas, Renewable Energy, Power Systems)

✅ Key Skills to Develop:

• Mathematical modeling of energy markets
• Optimization (linear/nonlinear programming), simulation techniques
• GIS software (for geospatial data analysis)
• Python, MATLAB, Power BI

✅ What to Do:

• Take Energy Economics, Petroleum Engineering, or Renewable Energy courses
• Gain knowledge of reservoir modeling, power grid optimization
• Get familiar with industry standards (ISO, NERC, OPEC reports)
• Apply for Energy Data Analyst, Market Analyst, Optimization Engineer roles

🔗 Where to Apply: ExxonMobil, Shell, Chevron, Schlumberger, BP, Siemens Energy, Tesla

 Example Role: Energy Data Analyst at BP - Analyze oil and gas production data for optimization - Develop machine learning models to predict energy market trends - Use MATLAB and Python for real-time data visualization 

4. Healthcare (Bioinformatics, Biostatistics, MedTech)

✅ Key Skills to Develop:

• Biomedical signal processing (wavelet-based noise reduction)
• Statistical modeling for clinical trials
• Image processing (MRI, CT scans) using deep learning
• Python, R, MATLAB, TensorFlow, SciPy

✅ What to Do:

• Apply for NIH (National Institutes of Health) or hospital-based research projects
• Get certifications in healthcare analytics, epidemiology, or clinical research
• Work on healthcare AI projects (e.g., disease prediction models)
• Apply for Biostatistician, Clinical Data Scientist, Bioinformatics Engineer roles

🔗 Where to Apply: Johnson & Johnson, Pfizer, Medtronic, GE Healthcare, Mayo Clinic

 Example Role: Biostatistician at Pfizer - Conduct statistical analysis for clinical trial data - Develop predictive models for patient outcomes - Work with epidemiologists and medical researchers on AI-driven healthcare solutions 

5. Oil Industry (Data Science, Engineering, Reservoir Modeling)

✅ Key Skills to Develop:

• Data analytics in drilling, reservoir simulation
• Seismic data interpretation, petroleum economics
• Python, MATLAB, GIS, geostatistics, machine learning
• Industry software: Petrel, Schlumberger software

✅ What to Do:

• Take oil & gas analytics or petroleum engineering courses
• Gain experience in geostatistics, subsurface modeling
• Apply for Data Analyst, Petroleum Economist, Reservoir Engineer roles

🔗 Where to Apply: Halliburton, Schlumberger, Baker Hughes, TotalEnergies

 Example Role: Reservoir Engineer at Schlumberger - Design numerical simulations for oil extraction - Analyze geostatistical models for drilling site selection - Develop Python-based tools for real-time reservoir monitoring 

General Actions to Improve Job Prospects:

• Enhance your LinkedIn & ResearchGate profiles
• Apply for internships & entry-level roles
• Consider short-term contracts, internships, and consulting work
• Contribute to open-source & Kaggle competitions
• Build a portfolio with finance models, AI projects, or energy simulations

By Youssaf Menacer, Ph.D.