Principal Data Scientist
Are you a hands-on data scientist with deep expertise in NLP and LLMs, strong Python coding skills, and a track record of deploying models to production? Do you thrive in building real-world AI solutions that are used by actual customers? If so, we’d love to talk to you! Role summary: As a Principal Data Scientist (individual contributor), you will play a hands-on role in designing, building, and deploying scalable AI solutions that go beyond prototypes and are actively used in production. You’ll work closely with collaborative teams to co-develop innovative products for financial markets and professionals. We’re looking for someone who combines deep technical expertise in NLP and LLMs , strong Python engineering skills , and real-world experience shipping and supporting models in production . You should be comfortable owning delivery timelines and ensuring that solutions meet business needs and production-grade standards. What you'll be doing: This is a hands-on technical leadership role in a high-impact environment focused on delivering production-ready AI systems.
- Lead the end-to-end development of AI solutions: design, build, test, and deploy models that are robust, scalable, and used by real users.
- Apply NLP and LLM techniques to solve real-world problems, ensuring models are optimized for performance and reliability.
- Continuously improve model quality through tuning, evaluation, and feedback from production usage.
- Evaluate third-party AI solutions with a critical eye on performance, scalability, and integration into production environments.
- Write and maintain production-grade Python code, adhering to best practices in software engineering and model development.
- Collaborate with engineering and business partners to define requirements, shape roadmaps, and ensure successful delivery of AI products.
- Extensive hands-on experience applying NLP and LLMs to real-world problems, with a consistent track record of shipping models to production and supporting them post-deployment.
- Strong Python programming skills, including object-oriented design and proficiency with key ML libraries (e.g., PyTorch, TensorFlow, Scikit-Learn).
- Solid understanding of probability and statistical modeling to support robust model development and interpretation.
- Experience with cloud platforms (especially Azure and/or AWS) and modern deployment practices for scalable AI delivery.
- Proven ability to set and uphold coding and model evaluation standards for production environments.
- Excellent communication skills to articulate technical decisions and trade-offs to both technical and non-technical audiences.
- Familiarity with DevOps practices including CI/CD, version control, automated testing, and monitoring to support reliable model deployment and maintenance.
- High-impact projects: Work on innovative AI products that solve complex, high-value challenges using rich datasets.
- Competitive benefits: Strong compensation, comprehensive benefits, and investment in your career growth.
- Industry leadership: Be a founding member of a team delivering novel products that democratize modeling and analytics.
- Collaborative environment: Join a team of experienced engineers in a culture of continuous learning and development.