Senior Scientist, Analytical Chemistry

Lila Sciences Lila Sciences · AI Frontier · Alewife, Cambridge, MA · Autonomous Science Platform

Develop and deploy advanced analytical and characterization strategies to support Discovery Chemistry efforts, focusing on small molecules. Establish and scale multimodal characterization workflows, integrating with AI/computational teams for platform learning and iterative design-make-test-analyze cycles.

What you'd actually do

  1. Develop, optimize, and implement analytical and multimodal characterization workflows to support Discovery Chemistry programs and molecular discovery campaigns.
  2. Support the design, synthesis, screening, and optimization of small molecules by delivering rapid, reliable, and information-rich analytical data.
  3. Lead analytical method development for compound identification, purity assessment, impurity profiling, reaction monitoring, and molecular characterization using techniques such as liquid chromatography, mass spectroscopy, NMR, and complementary orthogonal methods.
  4. Build characterization strategies that extend beyond traditional analytical methods, incorporating multimodal measurements that provide deeper insight into molecular identity, reaction outcomes, physicochemical properties, and structure–function relationships.
  5. Partner closely with Discovery Chemistry and screening teams to support high-throughput screening and high-throughput experimentation workflows, including rapid sample analysis, reaction triage, and compound profiling.

Skills

Required

  • PhD in Analytical Chemistry, Organic Chemistry, Pharmaceutical Sciences, Chemical Biology, or a related scientific discipline with 5–8+ years of relevant industry or high-performance research experience.
  • Deep expertise in analytical chemistry and molecular characterization in support of chemistry-driven discovery efforts.
  • Strong hands-on experience with key analytical techniques for small molecule analysis.
  • Demonstrated experience developing analytical methods for compound characterization, reaction monitoring, impurity analysis, and purity assessment.
  • Experience supporting Discovery Chemistry, medicinal chemistry, synthetic chemistry, or other molecule-focused R&D environments.
  • Strong understanding of how analytical data informs compound progression, screening decisions, reaction optimization, and molecular design.
  • Experience working with or supporting high-throughput workflows, including rapid analytical turnaround in fast-paced research settings.
  • Ability to solve complex analytical problems independently and work effectively across interdisciplinary teams spanning chemistry, screening, automation, and computational sciences.
  • Strong documentation, communication, and data interpretation skills, with a commitment to rigor, reproducibility, and scientific quality.

Nice to have

  • Experience with multimodal characterization approaches that combine orthogonal measurements to generate deeper insight into molecular systems and discovery workflows.
  • Experience supporting high-throughput screening, reaction screening, or automated discovery platforms.
  • Familiarity with analytical workflows integrated with robotics, liquid handlers, autosamplers, or other automation-enabled laboratory systems.
  • Experience working in AI-enabled or highly data-driven R&D environments where experimental data is used to drive predictive modeling or closed-loop optimization.
  • Knowledge of characterization approaches that extend beyond traditional compound QC, including molecular profiling, reaction analytics, and property-focused measurements.
  • Familiarity with data systems such as ELNs, LIMS, and software tools used to manage and analyze large analytical datasets.
  • Ability to operate effectively in a fast-moving, innovative environment with evolving platform needs and cross-functional priorities.
  • Strong scientific curiosity and interest in building next-generation analytical capabilities for molecular discovery.

What the JD emphasized

  • multimodal characterization workflows
  • high-throughput workflows
  • AI-enabled