Junior Financial Data Scientist/ Quantitative Risk Analyst

About Aris Investing: **
Aris Investing LLC is a dynamic and innovative investment management firm specializing in technology-enabled sub- advisory services. We empower financial advisors to optimize client portfolios for personalized and efficient growth through cutting-edge machine learning and quantitative techniques. Job Description: Aris Investing is seeking a talented and motivated Machine Learning and Quantitative Analyst with 1-3 years of experience in applying machine learning or other quantitative techniques using Python, specifically in the financial domain. The ideal candidate will have a strong background in optimization techniques and a passion for leveraging data- driven insights to enhance investment strategies.
**Responsibilities:
1.Develop and implement machine learning models for predictive analytics in the financial domain.
2.Apply quantitative techniques to analyse and optimise investment portfolios, contributing to the enhancement of portfolio performance.
3.Collaborate with the investment team to identify opportunities for the application of machine learning in decision-making processes.
4.Conduct research on market trends, financial data, and emerging technologies to stay at the forefront of quantitative analysis in finance.
5.Work with large datasets to extract meaningful insights and develop strategies to improve investment decision-making.
6.Collaborate with cross-functional teams to integrate machine learning models into existing financial systems.
7.Implement and maintain data pipelines for efficient data processing and model deployment.
8.Stay informed about advancements in machine learning and quantitative finance to continuously improve and innovate Aris Investing's analytical capabilities.
Qualifications:
1.Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Finance, or a related field.
2.Strong programming skills in Python, with experience in data manipulation, statistical analysis, and machine learning libraries (e.g., NumPy, Pandas, Scikit-Learn, TensorFlow).
3.Solid understanding of quantitative finance concepts and techniques, with hands-on experience in applying optimization methods.
4.Experience working with financial data and a familiarity with market structures, asset classes, and risk management.
5.Strong analytical and problem-solving skills, with the ability to translate complex ideas into actionable insights.
6.Effective communication skills with the ability to convey technical concepts to both technical and non-technical stakeholders.
7.Proven ability to work collaboratively in a team environment and contribute to the development of innovative solutions.

Preferred to have:

• Understanding of different risk models like the Factor Risk Model
• Pursuing CFA certification/ MBA Finance Python coding experience