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' 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.

The ideal candidate is experienced with building systems that enable efficient and relevant retrieval of information from unstructured text, using a combination of NLP techniques and search.

What You Will Do:

• Explore different methodologies to extract, store and maintain important attributes from large volumes of unstructured data to facilitate fast and accurate information retrieval.
• Using statistical or algorithmic means to measure and maintain integrity and correctness of data.
• Leverage ontologies, data analytic skills to reveal data patterns, formulate hypotheses and draw sound conclusions from analysis and experiments.
• Carry an open, inquisitive mind, willingness to learn, dive deep and strive to use innovative techniques to solve difficult problems.

Required Qualifications:

• PhD, or Masters with 2+ years, or Bachelor with 3+ years experience in a quantitative or computational field such as Computer Science, Engineering, Physics, Machine Learning, Statistics, or related field.
• Experience in modern Deep Learning and Natural Language Processing (NLP) techniques and frameworks, tokenization, text preprocessing and analytics, Exploratory Data Analysis (EDA)
• Experience with designing, processing and maintaining search indices on rising volume of unstructured documents with varying lifespans.
• Proficient with python, pandas, numpy, elastic search.
• Experience in frameworks like Pytorch, Tensorflow, or Keras.
• Strong programming skills, familiarity with software development cycles, solid understanding of software concepts - data structures and algorithms.
• Team player mindset and ability to work in an interdisciplinary team.
  

Preferred Qualifications:

• Understand how to leverage word embeddings, entity extraction, relations extraction, text classification and text analytics.
• Operational experience with Elasticsearch and/or Solr.
• Understand BERT architecture and its variants, experience with huggingface framework
• Working knowledge of AWS, GCP, data warehousing.
• Experience using biomedical knowledge information systems, such as UMLS, SNOMED CT, and RxNorm
• Clinical/Healthcare domain experience especially in oncology and/or genomics.

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