Data Scientist

No sponsorship can be provided for this position

No C2C

This is a newly established team and you will join it as key founding member. As a Data Scientist , you play a leading role in shaping and executing data-driven strategy, specifically in asset management area. You will partner with other cross-functional teams, data engineers, financial analysts and business leaders to shape the future of the data landscape. This role leads the development of advanced data science projects and data driven insights to significantly elevate business outcomes. You will solve meaningful business problems using generative AI, and advanced machine learning models.

This role is based in our client's office in Newark, NJ. Their organization follows a hybrid work structure where employees can work remotely and/ from the office, as needed, based on demands of specific tasks or personal work preferences. This position is hybrid and requires your on-site presence on a reoccurring weekly basis 3 days per week and can change based on future updates to the company’s in-office presence policy.

Responsibilities

• Lead the development and optimization of Generative AI (Gen AI) models, including LLM fine-tuning, Retrieval-Augmented Generation (RAG), and AI-driven quantitative research.
• Research and implement AI-related strategies, leveraging LLMs, NLP, and alternative data sources to drive investment decisions.
• Develop and integrate machine learning-based market models, optimizing business growth and profitability.
• Collaborate with engineering, and investment teams to deploy production-ready AI solutions for financial applications.
• Optimize AI models for efficiency, leveraging advanced techniques such as quantization, low-rank adaptation (LoRA), and knowledge distillation.
• Stay at the forefront of Gen AI innovations to enhance financial insights and drive automation in portfolio management.

Qualifications

• PhD or Master’s degree in Computer Science, Machine Learning, Engineering, Applied Mathematics, or comparable quantitative disciplines.
• 3 years of experience in developing LLM, NLP, NLU, NLG, deep learning models, and transformer models, with a focus on developing conversational AI solutions.
• 3 years of experience in retrieval-augmented generation (RAG), vector embeddings, and knowledge graphs.
• Hands-on experience with machine learning development and AI explainability methods, i.e. reinforcement learning, transfer learning, counterfactual analysis, model drift detection, adversarial testing, etc.,
• Preferably 3 years of experience with model optimization techniques (e.g., distillation, quantization, model pruning).
• Preferably strong knowledge of Gen AI application in financial industry, but not required.
• Proficiency in Python, PyTorch, TensorFlow, Hugging Face Transformers, and distributed computing frameworks.
• Hands-on experience integrating alternative data sources, including news analytics, satellite data, and financial reports, into AI-driven trading models.
• Excellent documentation, communication and presentation skills, can influence without authority
• Team-orient mindset and can-do attitude