Passionate about using clinico-genomics to develop new therapies for cancer?

Tempus is a technology company at the forefront of the expansion of multi-modal healthcare data generation and the application of artificial intelligence (AI) to fundamentally change cancer care.  Tempus is growing, and we are seeking exciting new talent to join the team.

Tempus' proprietary platform connects an entire ecosystem of real world data to deliver real-time, actionable insights enabling physicians to drive better outcomes through precise, individualized care.  Our data accelerates the pace of innovation, empowering researchers to characterize disease, discover new opportunities, maximise clinical trial success, and ensure the right therapies reach the right patients.

Excitingly Tempus is expanding and opening a new office in Boston/Cambridge MA.  We are looking for talented Real World Evidence Scientist to join our team. In this role, the successful candidate will collaborate in major strategic alliances with a world leading biopharmaceutical organization.  As a Tempus employee you will have access to the world’s largest real world patient clinical data set linked to genetics, transcriptomics and digital pathology.  Utilizing Tempus’ data and platforms, you will deliver transformational impact across the entire drug R&D lifecycle.  You will also develop methodology and algorithms advancing cancer precision medicine for patients across the Tempus network. 

Responsibilities:

• Partner with a major pharma client to design, develop and execute real world and clinical data research leveraging the Tempus platform to advance drug R&D programs.

• Become an expert converting Tempus’ real world data into real world evidence and insights.

• Become an expert in the pharma clients’ strategies, trials and pipeline to identify where the Tempus platform can add value.

• Collaborate with the pharma client’s medical, scientific and technical teams to co-architect solutions and projects.

• Dive into raw data sources to abstract new value beyond standard data pulls.

• Combine data from EMR’s, observational notes, claims and other databases at the patient level for analysis.

• Deliver advanced analysis of real world and clinical data to discover new research opportunities, run clinical trial simulations, perform endpoint (e.g. survival) analysis, and identify epidemiological trends.

• Guide clinical and epidemiological study designs using real world evidence and statistical principles

• Collaborate with, educate and receive mentorship from interdisciplinary experts in engineering, medical and data sciences.

• Document, summarize and communicate highly technical results and methods clearly to non-technical audiences.

• Drive continual improvement of the Tempus platform.

• Help build Tempus’ reputation within the Greater Boston biotech and tech community.

• Author whitepapers and peer reviewed manuscripts.

Preferred Qualifications:

• PhD (or Masters and 2+ years of employment) in a directly relevant field

• quantitative and computational skills e.g. Mathematics, Biomedical Informatics, Biometrics, Data Science for Health or similar.

• life science knowledge e.g. Medical, Oncology, Immunology, or similar

• Comfort in a client facing role and interdisciplinary working

• Hands-on experience with real world data derived from electronic medical records, observational studies, clinical/pathology notes and disease registries

• Proven track record impacting real world, clinical trial or pharmaco-epidemiology studies through application of statistics / machine learning / data science

• Experienced with clinical outcome modelling, e.g. survival analysis, in sparse data

• Proficient in R / Python, and excited to code

• Proficient in SQL

• Experience in multiple of:

• Phenotypic network analysis (e.g. topological, graph or bayesian)

• Population analysis

• EMR data abstraction

• Digital twins

• Genomic data analysis

• Clinical data standards

• Clinical trial design and statistics

• Biometrics

• Medical terminologies and controlled vocabularies (ICD9/10/SNOMED)

• Drug R&D

• Oncology or Immunology

• Health economics

• Insurance claims databases

• Statistical analysis plans (SAP) and clinical trial protocols

• Advanced visual analytics 

• Thrive in a fast-paced environment and willing to shift priorities seamlessly.

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