Senior Data Scientist, Applied AI

Company Summary

Lila Sciences is a privately held, early-stage technology company pioneering the application of artificial intelligence to transform every aspect of the scientific method. Lila is backed by Flagship Pioneering, which brings the courage, long-term vision, and resources needed to realize unreasonable results. Join our mission-driven team and contribute to the future of science.

Our Life Sciences effort is leveraging AI and high-throughput automation for valuable therapeutic discovery and development across biological modalities.

At Lila, we are uniquely cross-functional and collaborative. We are actively reimagining the way teams work together and communicate. Therefore, we seek individuals with an inclusive mindset and a diversity of thought. Our teams thrive in unstructured and creative environments. All voices are heard because we know that experience comes in many forms, skills are transferable, and passion goes a long way.

If this sounds like an environment you’d love to work in, even if you only have some of the experience listed below, please apply.

The Role:

We are seeking a  Senior Data Scientist to join our Applied AI group and lead data-driven initiatives that enhance our Large Language Model (LLM) capabilities and advance our mission toward Scientific Superintelligence. In this role, your primary focus will be collecting, monitoring, and analyzing chat logs to uncover actionable insights for continuous LLM refinement. You will collaborate closely with software engineers, ML researchers, and domain scientists to design analytical workflows, evaluate model performance in real-world settings, and help instill best practices for data-centric decision-making in AI. 

 Key Responsibilities: 

• Data Collection & Analysis: Gather and preprocess large volumes of internal chat logs, applying statistical methods and NLP techniques to uncover trends, patterns, and areas for LLM improvements. 

• LLM Evaluation & Optimization: Design and implement experiments to assess model performance, guiding model tuning and feature enhancements based on empirical evidence. 

• Cross-Functional Collaboration: Work alongside Data Engineers and ML researchers to build robust data pipelines; translate insights into data-driven recommendations for stakeholders across the organization. 

• Data Visualization & Reporting: Develop dashboards and visualizations that effectively communicate complex findings to both technical and non-technical audiences, facilitating informed decision-making. 

• Statistical Modeling & ML: Apply machine learning techniques to generate predictive insights, explore generative AI methods, and validate data-driven hypotheses. 

• Continuous Improvement: Champion best practices in reproducible research, version control, and documentation to ensure reliability and scalability of data workflows. 

Qualifications: 

• Educational Background: Ph.D. or Master’s degree in a scientific field of study. 

• Professional Experience: 3+ years of industry experience in data science, analytics, or ML model development—ideally in a production environment. 

• Technical Proficiency: 

• Python & OOP: Strong Python skills with a solid grasp of object-oriented programming principles. 

• ML & Statistical Methods: Hands-on experience in machine learning, data analysis, and statistical modeling. 

• NLP: Familiarity with natural language processing techniques, especially for text data analytics and model evaluation. 

• Data Analysis & Visualization: Proven ability to transform raw data into actionable insights using modern data analysis libraries (e.g., Pandas, Plotly, or similar). 

• Communication & Collaboration