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Job Summary
The Global Markets Data Analytics department focuses on enhancing data quality and analytics capabilities within the organisation. The team collaborates closely with various departments, including Sales, Trading, and IT, to ensure data integrity and provide actionable insights. The team is responsible for managing data from various sources, including Mopani, Refinitiv, Bloomberg, and others, to support electronic trading and market analysis.Assist in the development and optimization of market-making models, focusing on equities and equity derivatives. Conduct back testing and research to improve current models and develop new ones. Analyse high-frequency trading data to identify patterns and trends. Implement machine learning techniques, particularly LSTMs and convolutional networks, to predict short-term price movements. Collaborate with teams to integrate new indicators and models into production environments. Work with AWS infrastructure, including S3 buckets and Sage Maker, for data processing and model training, or possibly an alternative similar platform. Generate and analyse data samples, including time-based and volume-based sampling. Ensure the robustness of models by balancing in-sample and out-sample results. Key Projects: Expanding the universe of stocks traded by the current algorithm, creating new algorithms and possibly updating current sell-side / trader algos (market making). Incorporating trading indicators and market trends into existing models. Developing stationary indicators to predict price movements. Collaborating with the data analytics team to optimize model performance.
· Assist in the development and optimization of market-making models, focusing on equities and, equity derivatives.
· Conduct back testing and research to improve current models and develop new ones.
· Analyse high-frequency trading data to identify patterns and trends.
· Implement machine learning techniques, particularly LSTMs and convolutional networks, to predict short-term price movements.
· Collaborate with teams to integrate new indicators and models into production environments.
· Work with AWS infrastructure, including S3 buckets and Sage Maker, for data processing and model training.
· Generate and analyse data samples, including time-based and volume-based sampling.
· Ensure the robustness of models by balancing in-sample and out-sample results.
Preferred Qualifications:
· Familiarity with cloud technologies and their application within the financial services sector.
· Strong background in machine learning, particularly in time series analysis and neural networks.
· Experience with high-frequency trading data and market microstructure.
· Proficiency in Python and familiarity with AWS services, especially Sage Maker.
· Ability to work with large datasets and perform data normalization.
· Knowledge of technical indicators and their application in equity markets.
· Strong analytical and problem-solving skills.
· Excellent communication skills to collaborate with cross-functional teams.
Experience:
o Minimum 5-7 years of experience in data analytics, machine learning, quantitative analysis.
o Proven experience working in complex financial systems and applications (e.g., trading platforms, payment systems, risk management systems).
o Strong understanding of financial products, capital markets, derivatives, and treasury operations.
o Strong understanding of Equities and trading
o Hands-on experience with coding in Python, and the use of visualisation tools
· Must have experience with Machine Learning
· Must have knowledge of Market Microstructure
- Technical Skills:
o Proficiency in SQL, Python, AWS, and Quick sight; experience working with databases for data analysis. 5+ years
o Knowledge of statistical and ML (machine learning) techniques
o Experience with ticketing systems (e.g., Azure Devops (ADO), ServiceNow), change management tools
o 5+ Years of experience within global markets
o Proficiency in machine learning A MUST
o Proficiency in trading algos A MUST
- Soft Skills:
o Strong analytical and problem-solving skills with the ability to troubleshoot complex issues in high-pressure environments.
o Excellent communication and interpersonal skills, with the ability to interact with both technical teams and business stakeholders.
o Strong organizational skills with attention to detail and the ability to manage multiple priorities.
o Proactive, self-motivated, and able to work independently and as part of a team.
Deep understanding of financial products, trading systems, pre- and post-trade and high frequency data techniques
Ziyasiza Consulting (Pty) Ltd
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