Data analyst with finance background ( financial markets ) , dashboarding , Gen AI
Must have : Skills: python, machine learning, SQL, Tableau, Power BI, Generative AI (GenAI), NLP, Computer Vision, hypothesis testing, communication, visualization, financial markets, transformer, deep-learning.
Responsibilities
1. Drive analytic projects for all pillars of the bank’s treasury and markets department, such as bond analytics, news generation FX trading signals, product recommendation and customer hyper-personalization.
2. Create appropriate data visualisations, utilising PowerBI, Tableau and other appropriate tools like Python for effective storytelling.
3. Utilize advanced statistical and machine learning methods to derive insights and predictions from large volumes of transactional, operational and customer data.
4. Translate complex findings into intuitive visualizations and recommendations for front office traders and senior management.
5. Write and refactor code into reusable libraries/ APIs/ tools, deploy machine learning ecosystems/ pipelines and perform sub-system integration as required.
6. Participate in Generative AI (GenAI) and Document AI (DocAI) initiatives for news recommendation, customer pitch generation and market data collation.
7. Perform hypothesis testing and experimentation to discover causal drivers for customer and market behaviours.
Required Experience
1. Bachelor/ masters in a quantitative discipline, such as Mathematics/Statistics, Business Analytics, Computer Science, Engineering, or equivalent experience.
2. Working knowledge in data visualization tools such as PowerBI, Tableau or equivalent
3. Expert working knowledge and hands-on experience using Python and SQL.
4. Demonstrable understanding and application of varied AI/ML concepts and models, their mathematical underpinnings, and trade-offs
5. Practical experience using quantitative and statistical techniques to solve business problems such as hypothesis testing, regression, causal and correlation analysis, etc.
6. Excellent verbal and written communication skills to explain insights from technical work to non-technical audience through presentation or other means.
7. Experience working with unstructured data (text, images, audio) and application of NLP/ Computer Vision techniques and deep-learning and transformer models.
