Tempus
Prior Listings
- Machine Learning Engineer (NLP)
- Machine Learning Engineer, MLOps
- Analytics Manager, Translational Research
- Real World Data Scientist
- Staff Machine Learning Scientist, Generative AI
- Real World Data Scientist
- HR Data Analyst, People Team
- Staff Machine Learning Scientist (Cardio)
- Real World Data (RWD) Scientist
- Bioinformatics Analyst - Quality Control/Variant Interpretation
- Data Analyst, Commercial Feasibility Analytics
- Director, Data Science Operations
- Machine Learning Scientist, Generative AI
- Machine Learning Scientist, Generative AI
- Data Scientist II, Outcomes Research
Director, Data Science Operations
Director, Data Science Operations
Passionate about precision medicine and advancing the healthcare industry?
Recent advancements in underlying technology have finally made it possible for AI to impact clinical care in a meaningful way. Tempus' proprietary platform connects an entire ecosystem of real-world evidence to deliver real-time, actionable insights to physicians, providing critical information about the right treatments for the right patients, at the right time. Our team partners with scientists at biotechs and pharma companies who are using our real-world clinical data to understand treatment patterns and study outcomes.
We are seeking a Director, Data Science Operations to join our AI and Data Science (AI/DS) team. As the Director of Data Science Operations, you will lead data initiatives for internal stakeholders in AI/DS. This expert will set up processes and infrastructure including using machine learning to monitor the quality of EMR and integrated third-party data such as claims data which are utilized by AI/DS. This individual will serve as the voice of AI/DS on cross-functional teams serving to improve data quality. In addition, this role will have oversight of a team responsible for provisioning patient cohorts of interest for retrospective studies. Strong candidates will have prior experience working in the healthcare industry, or in a similar capacity as a consultant or domain expert.
Responsibilities:
- Lead initiatives around benchmarking and improving data quality that impact AI/DS
- Serve as VOC on cross-functional teams and develop strong relationships with Alliance Management, RWD Engineering and peers in AI/DS
- Lead standardization of cohort provisioning (i.e., patient selection) for retrospective studies using Tempus database
- Develop and mentor a team of direct reports
Suggested Qualifications:
- MS/PhD degree in a quantitative discipline (e.g. statistical genetics, cancer genetics, machine learning, bioinformatics, statistics, computational biology, biomedical informatics, or similar)
- 5+ years of supervisory experience
- 5+ years of related experience. Experience with genomic (e.g., DNA-seq, RNA-seq) or clinical (survival data, trials, real world evidence, claims) data, and familiarity with methods for time to event analysis (Kaplan-Meier, Cox regression) desirable
- Strong programming skills and experience with the python clinical+molecular data science stack: Pandas, NumPy, SciPy, Scikit-learn, lifelines, and Jupyter. Experience with R is desirable.
- Strong database and SQL skills (BigQuery, dbt)
- Experience with engineering best practices for research computing (docker, git, code review, workflow managers, linux, cloud computing)
- Demonstrated experience in building pragmatic solutions and long-term scalable designs
- Thrive in a fast-paced environment and able to shift priorities seamlessly
- Strong attention to detail, specifically in the realm of clinical data models, data quality, consistency, etc.
- Excellent communication skills with demonstrated ability to influence stakeholders and collaborators from a broad range of backgrounds (medical/scientific/engineering, etc.)
- Demonstrated ability to successfully navigate ambiguity and complexity
- Team player mindset and ability to work in an interdisciplinary team
- Goal orientation, self motivation, and drive to make a positive impact in healthcare