Our client is a highly specialized investment firm, focusing on innovating the private equity and venture capital space. They are at the forefront of financial technology, investing in companies that deliver mission-critical software, information, and services across key sectors including Banking & Payments, Capital Markets, Data & Analytics, Insurance, and Investment Management
We seek a skilled Senior Data Scientist to spearhead the development of an AI-driven Financial Advisor co-pilot. In this role, you will be responsible for building predictive models that will shape the future of wealth management products. This is an exciting opportunity to work on cutting-edge technology, leveraging your expertise in machine learning to create innovative solutions for the financial services sector.
The ideal candidate has deep experience in machine learning and has been exposed to full-stack applications.
Responsibilities
- Design, build, and implement AI Co-Pilots, specifically tailored for the Wealth and Asset Management industry.
- Lead the end-to-end development and deployment of predictive models for wealth management solutions, from database to user interface.
- Partner with the Director of Artificial Intelligence to conceptualize and execute a comprehensive strategy for integrating AI across business units.
- Rapidly prototype new algorithms and models, and transition from prototype to production environment, ensuring scalability and robustness
- Develop software solutions, including database schema design, back-end logic
- Measure and optimize the performance of both machine learning models and the full-stack applications, ensuring they align with business objectives.
- Collaborate with cross-functional teams to ensure that AI solutions enhance user experience and add significant business value.
- Act as a technical leader within the team, providing guidance and mentorship to other engineers.
Qualifications
- Proficiency with LLM frameworks, with experience in building applications that integrate complex large language models, utilizing retrieval-augmented generation for contextual search, and expertise in prompt engineering to optimize human-AI interactions.
- Proven track record of building and deploying machine learning models in a business context.
- Proficient in utilizing a range of machine learning libraries and frameworks (such as TensorFlow, PyTorch, Scikit-learn, Keras, etc.) to build, train, and deploy models efficiently.
- Strong software engineering skills, including proficiency in Python.
- Familiarity with cloud platforms (AWS, GCP, Azure) and understanding of containerization and orchestration tools (Docker, Kubernetes).
- Ability to rapidly prototype and innovate, while focusing on scalable solutions.
- Strong problem-solving skills and the ability to learn on the job, staying ahead of the latest industry trends.
- Self-starter, capable of learning on the job and adapting to new challenges.
Education
- Bachelor’s degree in Computer Science, Engineering, or a related technical field, providing a solid foundation in software development principles.
