UAE based - Data Scientist - Finance Applications, Macro Systematic - Global Fund - Up to $300 - 400k TC (tax free)
A global fund is looking for skilled Data Scientists at varying levels of seniority with a passion for finance and AI to join an innovative and expanding team in the UAE. The selected candidates will be at the forefront of refining large language model (LLM) outputs for financial applications. Example areas of interest include candidates with experience across macro data, systematic environments, NLP, GenAI, reinforcement learning, machine learning or financial/market data.
Total compensation (TC) can range up to $300k - 400k with potential to go higher for senior candidates. Relocation support provided.
Requirements & responsibilities can vary for different levels of candidates - if this seems like the right role for your experience, apply now!
Key Responsibilities:
- Oversee and enhance quality control systems for financial content generated by LLMs
- Develop quality metrics to evaluate the effectiveness and consistency of model-generated content
- Design and implement data pipelines for processing and analysing financial data
- Work closely with cross-functional teams to improve model performance, ensuring higher precision and relevance in financial contexts
- Apply domain expertise to enhance the financial knowledge representation in AI outputs
- Collaborate in an agile, technical environment with data scientists, engineers, and finance experts
- Generate descriptive statistics, uncover valuable patterns and present potential applications of datasets
Key Requirements:
- Ph.D. or Masters degree in Finance, Computer Science, Economics (Macro), or a quantitative field
- Strong grasp of macroeconomics, financial markets, and investment principles
- Proficiency in Python programming and SQL and experience with data manipulation libraries (such as pandas)
- Ability to design and implement efficient data pipelines and processing workflows to ingest new data sources.
- Strong problem-solving and analytical skills
- Knowledge of large language models (LLMs) and AI/ML optimization techniques (fine-tuning and architecture)
- Familiarity with natural language processing (NLP) and machine learning algorithms
