Press Ganey, the leading Human Experience (HX) healthcare performance improvement company, offers an integrated suite of solutions that address safety, clinical excellence, patient experience and workforce engagement. The company works with more than 41,000 healthcare facilities in its mission to reduce patient suffering and enhance caregiver resilience to improve the overall safety, quality, and experience of care. Press Ganey is a PG Forsta company.

Press Ganey is looking to hire a self-motivated senior machine learning data scientist with NLP experience. The primary goal is to analyze linguistic data and build, evaluate, and deploy ML models. An ideal candidate for this job would have some experience with healthcare facilities (hospitals, inpatient settings, outpatient settings, emergency departments), but that is not required. The role requires a high capacity for autonomy and the ability to creatively apply NLP techniques to novel problems.

Duties & Responsibilities

• Build, test, and deploy learning models on language datasets, writing sophisticated data analysis and machine learning code in Python and seeing models through to production.
• Assist in the identification and implementation of NLP analysis expansions and prototype additional NLP pipelines and models for additional or anomalous data types.
• Provide NLP analysis and general analytic support to QA team and others involved with data review or communication of analysis.
• Manage large language data annotation projects for model development and evaluation.
• Work with stakeholders to define the scope of novel projects.
• Closely collaborate with other data scientists as well as engineers.
• Interpret and communicate analytic approaches and results to analytical and non-analytical business partners and executive decision-makers.
• Document work.
• Mentor junior teammates.

Technical Skills

• Experience with ML (Scikit-learn) and deep learning frameworks (PyTorch or Tensor Flow)
• Familiarity and experience with neural networks and BERT-style language models.
• Information extraction evaluation (precision, recall, F1).
• Familiarity with word embedding algorithms and clustering methods, as well as more traditional statistical NLP approaches such as bag of words analyses and TF-IDF.
• Exposure and some experience with modern large language models, including the OpenAI family of models (ChatGPT, etc) or Med-PaLM.
• Experience with MLOps.
• Exposure to containerization and microservices.
• Familiarity with Databricks is a plus.

• Minimum of 5 years Data Science experience in an enterprise environment
• Bachelors degree in technology or like field required

All positions at Press Ganey require an applicant who has accepted an offer to undergo a background check. The specific checks are based on the nature of the position. Background checks may include some or all of the following: SSN/SIN validation, education verification, employment verification, and criminal check, search against global sanctions and government watch lists, fingerprint verification, credit check, and/or drug test. By applying for a position with Press Ganey, you understand that you will be required to undergo a background check should you be made an offer. You also understand that the offer is contingent upon successful completion of the background check and results consistent with Press Ganey's employment policies. You will be notified during the hiring process which checks are required for the position.

Press Ganey Associates LLC is an Equal Employment Opportunity/Affirmative Action employer and well committed to a diverse workforce. We do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity, veteran status, and basis of disability or any other federal, state or local protected class.

Pay Transparency Non-Discrimination Notice - Press Ganey will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor's legal duty to furnish information.

The expected base salary for this position ranges from $110,000 to $130,000. It is not typical for offers to be made at or near the top of the range. Salary offers are based on a wide range of factors including relevant skills, training, experience, education, and, where applicable, licensure or certifications obtained. Market and organizational factors are also considered. In addition to base salary and a competitive benefits package, successful candidates are eligible to receive a discretionary bonus or commission tied to achieved results.

All your information will be kept confidential according to EEO guidelines.

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