Copy of Staff Data Scientist

We’re looking for data scientists to join our team. You'll develop statistical, machine learning, and large language models (LLMs) to improve our operations platform and help us provide a better service to our clients. We're looking for generalist data scientists who are excited to jump into new problems, work cross-functionally, and write production-quality code.

About the Work:

• Leverage data to solve meaningful problems with appropriate complexity.
• Collaborate with a diverse team across engineering, PM, design, and operations to define a strategy and execute against it.
• Research operational/logistical problems and proactively identify potential solutions.
• Lead the design, implementation, and evaluation of descriptive, predictive, and generative models.
• Integrate machine learning and LLMs into user-facing applications to improve automation and personalization.
• Mentor and provide technical oversight on teammates' projects throughout the project lifecycle.
• Design and deploy LLM-powered solutions for text summarization, automation, and insights from unstructured data.
• Collaborate with product managers to develop AI-driven features that enhance decision-making and user experience.
• Work with MLOps engineers to scale, fine-tune, and optimize LLMs for efficiency and cost-effectiveness.
• Translate business objectives into machine learning solutions, ensuring alignment with stakeholder needs.

About You:

• Excellent communication skills with both technical and non-technical peers.
• Excellent mathematical and statistical fundamentals, including a degree in a quantitative field (such as Computer Science, Mathematics, Statistics, Economics, Physics) or equivalent professional experience.
• Wide-ranging professional experience solving complex business problems, and shipping/maintaining Python in a production environment.
• 5+ years of industry experience.
• Aptitude to rapidly iterate and deliver technical solutions that maximize business impact.
• Expertise with numerical software packages such as NumPy, scikit-learn, pandas, TensorFlow, or PyTorch.
• Experience with LLMs and NLP techniques such as fine-tuning models, RAG (retrieval-augmented generation), and vector embeddings.
• Strong experience developing and maintaining machine learning models in production, including API development, scaling, and monitoring.
• Ability to manage product ambiguity, seeking clarity when possible.
• Are accountable end-to-end for your own projects, through planning, deployment, maintenance, and monitoring. You spot and address potential issues early.

Bonus Points If You Have Experience With:

• LLM optimization (e.g., prompt engineering, fine-tuning, parameter-efficient tuning techniques).
• Designing systems to optimize portfolio allocation in a two-sided marketplace (E.g., matching demand & supply, automated financial incentives, hiring needs, demand forecasting).
• Using survival analysis and related methods to evaluate employee churn risk and predict future high-performers.
• Using NLP methods to build data products from unstructured sources (phone calls, website forms, internal documentation, etc.).
• Applying spatial statistics to incorporate geographic and regional differences in various problem contexts.
• Experience deploying ML & LLM models on cloud platforms (AWS, GCP, or Azure).