Translational Scientist, Applied Machine Learning and Agentic AI, Pharma R&D

Translational Scientist, Applied Machine Learning and Agentic AI, Pharma R&D

Location:

New York, NY

The Translational Scientist, Applied Machine Learning and Agentic AI will contribute to the technical development of cutting-edge agentic frameworks designed to automate the discovery of novel prognostic and predictive models in oncology. This role sits at the intersection of advanced Large Language Model (LLM) orchestration and computational biology. You will be responsible for building and refining "deep agents" capable of hypothesis generation, experimental design, and multimodal ML modeling utilizing foundation models.

In this role, you will be a key technical contributor, working closely with senior scientists and engineers to implement system designs and ensure code quality. You will apply advanced scientific methodologies to develop new predictive models and utilize causal inference frameworks to analyze vast multimodal oncology data, helping to scale scientific discovery from a manual process to a high-throughput, automated engine.

Responsibilities

• Agentic AI:
  Develop complex, state-of-the-art agentic workflows. Build agents capable of long-horizon planning, tool use and "co-scientist" reasoning.
• Multimodal Modeling:
  Leverage oncology foundation models to integrate DNA, RNA, H&E, and clinical data into predictive algorithms.
• Scientific Innovation:
  Collaborate with clinical scientists and pharma partners to define high-value use cases, such as clinical trial design support and treatment de-escalation.

Qualifications

• Education and experience:
  
  Minimum:
  PhD (or Masters degree with 3+ years of relevant experience).
• Combining:
  Quantitative and computational skills, specifically in AI agent based workflows (e.g. Applied Machine Learning, Generative AI, Mathematics, biostatistics). Biological, medical, or drug development knowledge and data (e.g. oncology, RWE, medical science, or clinical drug development).
• Technical/Scientific
  
  Skills:
  
  Agentic Frameworks:
  Proficiency in Python and orchestration frameworks, specifically Lang Graph (strongly preferred) or similar. Experience building deep agents with complex state management and graphs. LLM Application:
  Deep knowledge of prompt engineering, RAG (Retrieval-Augmented Generation), function calling, and evaluating non-deterministic LLM outputs.
• Machine Learning:
  Strong foundation in survival analysis (CoxPH, RSF) and evaluation metrics for oncology models.
• Software Engineering:
  Adherence to software best practices (unit testing, git) and experience designing scalable systems.
• Experience working with clinical trial or real-world data, clinical guidelines (e.g., NCCN for oncology) and emerging RWE methodologies Track record of success: proven in peer reviewed publications or other proven impact. Communication
  
  Skills:
  
  Excellent written and verbal communication skills, with the ability to present complex information clearly and persuasively to diverse audiences. Motivated:
  Thrive in a fast-paced environment and willing to shift priorities seamlessly.

Preferred Skillsets/Background Experience in integrative modeling of multi-modal clinical and omics data, preferably with multimodal embeddings and foundation models. Strong understanding of data and artificial intelligence in Oncology. Understanding of cancer biology and clinical data. Experience with deploying ML models in cloud environments.

CHI: $100,000-$150,000

NYC/SF: $120,000-$160,000

The expected salary range above is applicable if the role is performed from California and may vary for other locations (Colorado, Illinois, New York). Actual salary may vary based on qualifications and experience. Tempus offers a full range of benefits, which may include incentive compensation, restricted stock units, medical and other benefits depending on the position.

Additionally, for remote roles open to individuals in unincorporated Los Angeles – including remote roles
- Tempus reasonably believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment: engaging positively with customers and other employees; accessing confidential information, including intellectual property, trade secrets, and protected health information; and appropriately handling such information in accordance with legal and ethical standards.

Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law, including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.

We are an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.