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Background:
Our client is a global single-family office with a multi-asset investment strategy and a diversified international portfolio spanning real estate, luxury, energy across both private and public equities. As they broaden their mandate, they are seeking top-tier talent to join their team in the Middle East.
Reporting to the Chief Investment Officer, they are looking for a Data Analyst to be responsible for extracting, organising, processing, cleaning and validating investment-related data from multiple sources. The objective is to present this data in a clear, accurate and exhaustive manner in order to facilitate timely investment decisions.
Roles & Responsibilities:
- Enhancing data collection procedures in their systems to include information that is relevant for building analytic systems and managing their portfolio of investments
- Processing, cleansing, and verifying the integrity of data used for analysis
- Ensuring the availability, quality and security of data used by the Investment Team
- Data mining using state-of-the-art methods and extending company’s data with third party sources of information when needed
- Investigating and interpreting data to identify actionable insights and opportunities for improvement of the performance of our portfolio of investments
- Doing ad-hoc analysis and presenting results in a clear manner
- Presenting findings and recommendations to stakeholders in a clear and concise manner
- Creating automated anomaly detection systems and constant tracking of its performance
- Protecting data to ensure its confidentiality to the most stringent standards and divulging information on a need-to-know basis only
Your profile
- A bachelor’s or master’s degree in data science, computer science, statistics or a related field
- 5+ years of experience, with a minimum of 3 years in the financial industry
- Advanced knowledge of accounting and financial principles
- Proficiency in programming languages such as R or Java
- Good applied statistics skills such as distributions, statistical testing, regression, etc.
- Experience with data manipulation, cleansing, and analysis using tools such as SQL, Excel and other statistical software
- Understanding of Machine learning techniques and algorithms (K-NN, Naïve Bayes, SVM, etc.)
