SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Elucidata is a data-centric AI company making life sciences AI-ready. Headquartered in San Francisco with 120+ team members across the US and India, the company builds Polly, an AI-agentic platform that helps research teams wrangle, harmonize, and analyze biomedical data to accelerate drug discovery. Elucidata partners with 25+ leading organizations including Pfizer, Novo Nordisk, and Google DeepMind, and has been recognized by Fast Company as the "Most Innovative Biotech Company of 2024."
The Senior Scientific Manager will lead technical delivery of multi-omics and AI-driven solutions for BioPharma and biotech customers on the Polly platform. You will own customer relationships, lead a team of scientists, and set technical direction for transforming complex biomedical data into actionable insights. The role involves integrating multi-omics with clinical, literature, and genetic evidence—often through knowledge graphs—to answer target discovery and validation questions, while leveraging LLMs where they add value.
Key responsibilities include: end-to-end delivery leadership (scoping, experimental design, analysis, interpretation, and deliverables); setting analytical approaches for complex engagements; recruiting, mentoring, and managing a multidisciplinary team of bioinformaticians and data scientists; serving as the primary scientific point of contact for customer accounts; identifying and shaping upsell and cross-sell opportunities with the GTM team; staying current with emerging methods in target discovery and AI-driven drug discovery; owning resourcing, timelines, and stakeholder communication; and representing Elucidata externally through workshops, demos, presentations, and conferences.
You will work at the intersection of AI, biology, and impact, solving real-world challenges that accelerate the journey from data to discovery. Success is measured by growing, delighted accounts and a high-performing team that customers trust with their hardest problems.
REQUIREMENTS:
- Education & Experience: PhD with 5+ years, or Master's with 7+ years, of industry experience in Bioinformatics, Computational Biology, Genomics, or a related quantitative discipline.
- Customer & Delivery Leadership: Proven track record owning customer relationships and leading customer-facing delivery to successful, on-time outcomes.
- People Leadership: Experience building and managing interdisciplinary technical teams of scientists, bioinformaticians, and data scientists.
- Multi-omics Depth: Hands-on command of multi-omics NGS analysis—bulk and single-cell transcriptomics, spatial technology, genomics, and integrative multi-omics—applied to target discovery.
- Technical Leadership: Ability to lead integration of multi-omics with other biomedical evidence (clinical/real-world data, literature) to answer scientific questions for customers.
- Human-Genetics Evidence: Hands-on experience with genetic support for targets—GWAS/burden testing, Open Targets-style genetic evidence for target prioritization and de-risking.
- Applied LLMs: Experience using or leading LLM-based projects applied to real scientific or delivery problems.
- Programming: Strong hands-on ability in R and Python.
- Communication: Excellent stakeholder-management skills; ability to translate complex science for technical and business audiences.
- Commercial Mindset: Comfortable identifying and shaping upsell/cross-sell opportunities with GTM and Solution Managers.
Good to Have:
- Knowledge graphs for target discovery: designed biomedical graph data models embedding heterogeneous evidence; applied graph algorithms and graph ML; built evidence-integration and target-scoring frameworks.
- Perturbation biology & modeling: experimental (CRISPR screens, Perturb-seq) and/or computational perturbation-prediction approaches.
- LLM engineering depth: building RAG, agentic, or fine-tuned/evaluated LLM workflows on biomedical data.
- Scalable infrastructure: AWS/cloud and containerized pipelines (Docker, Nextflow/Snakemake).
- Publications: strong publishing record in peer-reviewed journals.
