Position Overview:

We are looking for a Data Scientist to join our innovative AI/ML team. You will play a key role in developing and deploying machine learning models, supporting our work in GenAI, machine learning (ML) development, and quantitative finance. You will work closely with engineers and business teams to implement state-of-the-art solutions that drive business value, focusing on quantitative models and AI-driven solutions for decision-making, optimization, and automation across the organization.

Key Responsibilities:

• Develop, validate, and deploy machine learning models tailored to quantitative finance applications, such as predictive models for pricing, risk management, and algorithmic trading.
• Collaborate with the ML Engineering team to build, test, and scale machine learning models in production, ensuring they meet performance, scalability, and reliability standards.
• Integrate GenAI solutions to enhance automation and generate insights from large datasets, leveraging advanced NLP techniques, text summarization, multimodal and multi-agent virtual assistant.
• Participate in the full lifecycle of model development: from data preprocessing, feature engineering, and model training to evaluation and deployment.
• Work closely with Quantitative Analysts to implement models for financial forecasting, portfolio optimization, iTracker and other quant-driven initiatives.
• Conduct research on the latest advancements in AI and machine learning to continually improve the performance and capabilities of our models.
• Design/optimize and implement data pipelines for processing large-scale financial and transactional data efficiently.
• Collaborate with cross-functional teams to ensure that data-driven insights and machine learning models align with business objectives.

Qualifications:

• Bachelor’s or Master’s degree in Data Science, Computer Science, Mathematics, Statistics, or a related field.
• 2+ years of experience in data science, quantitative finance, or machine learning role
• Strong programming skills in Python
• ⁠Experience in ML Engineering (MLOps), cloud platforms (AWS, Azure, GCP), and GenAI technologies.
• Knowledge of quantitative finance concepts is a plus
• Familiarity with GenAI technologies (such as GPT, transformer models) and applications like text summarization, natural language generation, or conversational AI.
• Strong communication skills, with the ability to collaborate with both technical and non-technical stakeholders.