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HomeCompaniesLila SciencesSenior Scientist, Analytical Chemistry

Senior Scientist, Analytical Chemistry

Lila Sciences · Cambridge, MA USA · Active · $148,000–$198,000 / year · Greenhouse

Job facts

FieldValue
CompanyLila Sciences
TitleSenior Scientist, Analytical Chemistry
Normalized title-
Department / teamAutonomous Science Platform
LocationCambridge, MA, United States
Work model-
Employment type-
Salary$148,000–$198,000 / year
Statusactive
ATS providerGreenhouse
Posted / first seen2026-03-25 / 2026-05-29
Changed / last seen2026-05-29 / 2026-06-06

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PageWhat it containsOpen
Company jobsActive postings from Lila Sciences.Open
Company breakdownsRole, location, ATS, and work model facets for this company.Open
ATS provider jobsActive postings observed through Greenhouse.Open
Provider filtered searchThe same provider as a filtered job collection.Open
City jobsActive postings in Cambridge.Open
Department jobsActive postings in Autonomous Science Platform.Open
Lifecycle eventsOpen, update, close, and reopen events for this posting.Open
Original postingCanonical source or apply URL captured from the ATS.Open

Linked records

CompanyLila Sciences
Sourcea1e67975-fd33-4f8d-940f-2dbc2480c450
ATS providerGreenhouse

Description

Your Impact at LILA The Senior Scientist, Analytical Chemistry will develop and deploy advanced analytical and characterization strategies to support Discovery Chemistry efforts across Lila’s platform, with a focus on enabling the rapid design, synthesis, screening, and optimization of small molecules and related molecular matter. This scientist will play a key role in generating high-quality, information-rich experimental data that informs chemistry decisions and accelerates platform learning. Working closely with Discovery Chemistry, automation, AI/computational, and screening teams, this role will establish and scale multimodal characterization workflows that go beyond traditional analytical chemistry approaches. The Senior Scientist will help build an integrated analytical capability spanning compound characterization, reaction monitoring, molecular profiling, and high-throughput data generation to support fast and iterative design–make–test–analyze cycles. This role will be critical to shaping Lila’s next-generation discovery engine by combining deep expertise in analytical chemistry with high-throughput experimentation, multimodal data generation, AI-enabled workflows. What You'll Be Building Develop, optimize, and implement analytical and multimodal characterization workflows to support Discovery Chemistry programs and molecular discovery campaigns. Support the design, synthesis, screening, and optimization of small molecules by delivering rapid, reliable, and information-rich analytical data. 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. 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. 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. Collaborate with automation and platform teams to integrate analytical instrumentation and data pipelines into robotics-enabled and scalable discovery workflows. Work closely with AI and computational teams to ensure analytical datasets are structured, interoperable, and useful for model development, closed-loop learning, and iterative molecule design. Establish robust workflows for reaction monitoring, in-process analytics, final compound quality assessment, and characterization of complex mixtures or intermediates. Troubleshoot analytical and characterization challenges related to sample preparation, instrumentation, method robustness, data interpretation, and workflow integration. Contribute to the development of platform-level capabilities for data-rich molecular discovery, including scalable characterization pipelines, method standardization, and best practices for analytical rigor. What You’ll Need to Succeed 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. Bonus Points For 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. Compensation We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact. U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program. International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market. Expected Base Salary Range $148,000 — $198,000 USD About LILA Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves. LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai. Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply. We’re All In Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy . A Note to Agencies Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.

Full job record

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Board IDa1e67975-fd33-4f8d-940f-2dbc2480c450
Providergreenhouse
Provider Job Key4192713009
TitleSenior Scientist, Analytical Chemistry
Normalized Title
Statusactive
Activeyes
Location TextCambridge, MA USA
DepartmentAutonomous Science Platform
Team
Employment Type
Workplace Type
Remote Policy
CountryUnited States
RegionMA
CityCambridge
Salary RawSalary Range $148,000 — $198,000 USD About LILA Lila Sciences is building Scientific Superintel
Salary Min148,000
Salary Max198,000
Salary CurrencyUSD
Salary Periodyear
Source URLhttps://job-boards.greenhouse.io/lilasciences/jobs/4192713009
Apply URLhttps://job-boards.greenhouse.io/lilasciences/jobs/4192713009
First Seen At2026-05-29 23:01:25Z
Last Seen At2026-06-06 07:34:08Z
Last Checked At2026-06-06 07:34:08Z
Last Changed At2026-05-29 23:01:25Z
Inactive At
Source Posted At2026-03-25 18:43:20Z
Source Updated At2026-05-14 21:07:37Z
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