Senior Data Scientist, LLM

In this role, you will have the opportunity to:

• Utilize large language models (LLMs) to transform various aspects of our business, including our product offering, customer service, and internal operations, making a tangible impact on our company and our customers.
• Guide and shape the future direction for the rapid adoption and application of LLMs within the organization, ensuring their use is both safe and effective.
• Take end-to-end ownership of the model building lifecycle, from the initial idea to production deployment, ensuring that our solutions are not only innovative but also reliable and sustainable.
• Continuously learn and stay updated with the latest trends in data science and fintech, especially in the world of LLMs, prompt engineering and productionalization of models. 
• Collaborate with domain experts and cross-functional teams to understand intricate problems specific to our industry, and identify opportunities where machine learning can drive significant innovation and efficiency.
• Leverage our state-of-the-art ML platform to monitor model performance post-production, with built-in triggers to identify model drift and opportunities for re-training, ensuring our solutions remain effective and relevant.
• Apply software engineering best practices, such as version control and continuous integration, to the code base; ensure that our models are not only effective but also well-tested, documented, and maintained.
• Embrace simplicity and effectiveness in your approach to challenges, adhering to the principle of Occam's razor to find the most straightforward solutions to complex problems.
• Teach and learn from your teammates. We believe in the power of collective knowledge and the importance of fostering a culture of continuous learning and mutual success

Skills we are looking for:

• Proven experience as an experienced data scientist or machine learning engineer, with a focus on Natural Language Processing (NLP), Reinforcement Learning (RL), or Large Language Models (LLMs).
• Proficiency in Python, with a strong familiarity with key data science & machine learning libraries and tools.
• Demonstrated experience in productionalizing ML models, with a track record of owning the full lifecycle of ML model development, from ideation to deployment and maintenance.
• Understanding of large language models such as GPT-4, Gemini, and others, with a deep understanding of their potential applications and limitations.
• Familiarity with key LLM concepts such as fine-tuning models, and libraries such as Langchain.
• Solid knowledge of data engineering and preprocessing, including handling large datasets, ensuring data quality, and managing data pipelines.
• Comfortable with software engineering best practices, including version control and using Git for collaborative development.
• Strong problem-solving skills, with the ability to think critically and creatively to find effective solutions to complex challenges.
• Excellent communication skills, with the ability to convey complex ideas in a simple, clear, and engaging manner for a variety of audiences.
• Outstanding interpersonal skills, demonstrated through the ability to thrive in highly collaborative settings and contribute positively to team-oriented environments.
• Familiarity with AI ethics and responsible AI practices, with a commitment to ensuring that our solutions are not only effective but also ethical and fair.