Data Scientist

4 weeks ago

Pittsburgh, United States Insight Global Full time

Must Haves:

  • Ph.D. in data science, statistics, or computer science OR equivalent
  • Background in Healthcare/familiar with healthcare data
  • 5+ years of experience in NLP model development, validation, extraction, maintain and deployment
  • Managerial Experience (this role has opportunity to become a lead in future of team)

Plusses:

  • Experience with Agile principles and development methodology

Day to day:

About UPMCE:

UPMC Enterprises (UPMCE) is the innovation, commercialization, and venture capital arm of UPMC, a $24 billion health care provider and insurer based in Pittsburgh, PA. With a mission to create products and businesses that make life-changing medicine happen, UPMCE invests financial and intellectual capital into developing solutions that benefit the entire health care industry with two broad focus areas: Digital Solutions and Translational Sciences. They have a diverse portfolio, supporting both early and growth stage companies with the wealth of expertise from UPMC.

The Hiring Team:

The Technology Solutions team offers technical and business services for UPMCE portfolio companies and investment partners creating innovative healthcare solutions to drive clinical and financial outcomes. They support all stages of a healthcare technology venture’s lifecycle with strategic, implementation, and operational services. The Data Analytics and Informatics Service within the Technology Solutions team provides key data-driven insights for both Digital Solutions and Translational Sciences focus areas to address critical business questions supporting investment and product development life cycles.

The Role:

The Data Scientist will play a vital role in providing insights for the cohort identification and manage the use of two vendor solutions, John Snow Labs and QuantPi. They will develop and implement advanced analytics techniques, and predictive modeling methodologies as part of the DPaaS initiative.

  • Text Data Collection and Preprocessing: Gathering, cleaning, and preprocessing text data from unstructured notes as part of DPaaS. This includes tasks such as tokenization, stemming, and handling text-specific challenges like dealing with different languages, slang, and abbreviations.
  • Model Development and Training: Designing, building, and training NLP models for de-identification of EMR data using techniques such as text classification, sentiment analysis, named entity recognition, machine translation, and language generation. This involves selecting appropriate algorithms, feature engineering, and fine-tuning model parameters.
  • Data Analysis and Insights: Analyzing data to extract meaningful insights and patterns that can inform business decisions. This includes performing statistical analysis, visualizing data, and communicating findings to stakeholders. Staying updated with the latest research and integrating state-of-the-art methods into projects.
  • Evaluation and Optimization: Evaluating NLP models using appropriate metrics (e.g., precision, recall, F1 score) and techniques (e.g., cross-validation, confusion matrix). Continuously optimizing models to improve accuracy, efficiency, and scalability.

What will these models be used for?

  • Building out an identification pipeline for EMR
  • They have data stored in tabular form, variable and patient identifier
  • Reports (blood reports, attached notes) - those live as PDF/Text documents
  • Building pipeline where we extract from EMR within database, de-identify database based on rules, when individual comes in they'll pick up that project

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