Senior Data Scientist

Phreesia is in the search for an experienced and hands-on Senior Data Scientist to join our growing Data Science Team and take part in our mission to activate patients and drive positive health outcomes! We’re looking for someone who has the analytical and technical skills to take ownership of business-critical data science projects for the entire lifecycle, from data exploration, modeling and analysis to model selection, validation, evaluation, and deployment.   

Picture yourself in a team of smart, humorous, quick-witted, and dedicated coworkers, all passionate about turning large sets of data into powerful insights that improve patient outcomes. You’ll be responsible for planning, building data products for internal consumption, near real-time business intelligence tools, and predictive models. But this role is not just about crunching numbers, we need you to organize complex data in a way that tells a compelling story and drives critical decision-making for stakeholders across and outside of the business. So, if you’re looking to be a part of cutting-edge clinical research on platforms exclusive to Phreesia, this may be the right opportunity for you.  

What You'll Do 

• Leverage Phreesia’s massive and ever-growing dataset to design and build data products that provide actionable business insights.   

• Use NLP techniques to parse, process, and structure textual data.   

• Develop methods to efficiently classify and characterize patient populations.   

• Optimize targeted engagement strategies through modeling, forecasting, and evaluation.   

• Navigate and use diverse machine learning stacks in Python and PySpark.   

• Quickly prototype ideas and solve complex problems by adapting creative approaches.   

• Take ownership of data products and ensure they are properly tracked throughout their lifecycle.   

• Ability to continually learn and try out the latest AI/LLM technologies

• Write clean, well-tested, code that will stand the test of time.   

• Be an expert communicator: you could summarize your daily progress in a tweet.   

What You'll Bring 

• Advanced degree in a quantitative field such as Data Science, Computer Science, Engineering, Mathematics, Statistics, Computational Linguistics, Physics, or related is required.  

• 5+ years of industry experience in an operational Data Science or ML Engineering role   

• Experience using NLP toolsets, such as Spark NLP, NLTK or spaCy 

• Excellent SQL and Python skills and experience using Apache Spark (Pyspark) for large data sets. 

• Fluency in Unix/Linux environments and software engineering practices (e.g. Agile, unit testing, code reviews, design documentation)

• Experience in using statistical principles to inform decision making (experimental design, significance tests, a/b testing)    

• Experience in collaborating with Data Scientists and Data Engineers to propose, test, validate, evaluate, and deploy Machine Learning models.   

• Experience using AWS services including S3, EMR, Glue, SageMaker, Redshift, and Athena or comparable services from other cloud providers.  

• Experience in one or more of the following: knowledge graphs, vector similarity search, causal inference, generative AI, and large language models.  

Base pay for US is $140,000 - $165,000 USD depending on qualifications.