Millennium is offering a Quantitative Research Intern position for its Dubai Off-Cycle program. This is a minimum 6-month full-time internship for STEM graduates, focused on quantitative finance, statistical modeling, and machine learning. The role provides hands-on experience in predictive data science, working collaboratively on feature engineering, novel machine learning algorithms, and return predictions.

Key Responsibilities:

• Collaborate with team members specializing in machine learning.

• Develop additional feature libraries for predictive models.

• Implement and test novel machine learning algorithms for return predictions.

• Manipulate and process multiple datasets, ensuring quality and usability.

• Apply statistical and quantitative finance techniques in research projects.

• Contribute to tools and processes to improve efficiency and scale research efforts.

Skills and Qualifications:

• Expert proficiency in Python.

• Strong experience with modern data science tools: Jupyter, pandas, numpy, sklearn.

• Degree in Mathematics, Computer Science, Statistics, or related STEM field from a top-ranked university.

• Knowledge of quantitative finance, mathematical modeling, statistical analysis, regression, and probability theory.

• Excellent analytical, problem-solving, and communication skills.

• Hands-on experience with predictive data science projects preferred.

• Ability to work independently and manage complex tasks in a fast-paced environment.

• Entrepreneurial mindset with strong curiosity and attention to detail.

Preferred Experience:

• Experience working with multiple datasets: assessing, cleaning, and creating features.

• Critical thinker, self-motivated, and eager to learn professionally.

About the Company:
Millennium is a global investment management firm that leverages advanced quantitative research, machine learning, and financial modeling to deliver innovative solutions. The Dubai internship program provides a collaborative environment to develop technical skills and apply them in real-world financial research projects.