- Take lead on data science projects to design and implement models and experiments from end to end, including data ingestion and preparation, feature engineering, analysis and modeling, model deployment, performance tracking and documentation.
- Lead-by-example junior data scientists around mature data science practices e.g. narrative-based ML specification, readable code, thorough documentation, comprehensive experimentation
- Work with a great deal of autonomy to convert ambiguous business problems in clear data science/ML specifications – Use contextual business acumen to convert model predictions/results into impactful insights and provide actionable guidance on risks and limitations
- Work hand-in-hand with product managers, software engineers, data engineers, subject matter to ship new models, algorithms and improvements continuously and collaboratively into production
- Use combination of machine learning knowledge and contextual business acumen to convert results into impactful insights and provide actionable guidance on risks and limitations from inference and chosen methods
- Write narrative documents for model specification and performance analysis to communicate findings and recommendations to teammates, stakeholders and executive leadership
You’ll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.
- Bachelor’s degree
- 5+ years of hands-on experience in data science and machine learning (specific areas of interest include anomaly detection, time-series/sequence models, NLP, uncertainty quantification, explainability methods, deep learning]
- Solid demonstrable proficiency in advanced data science tools such as Python, Spark, SQL
- Experience implementing predictive algorithms and associated statistical analysis/inference in a data science/ML workflow manipulating both structured and unstructured data
- Experience crafting and communicating highly technical results to a diverse audience
- Comfort working as part of a team and taking the lead, as opposed to solo projects
- Experience leading data science projects end-to-end including reviewing and elevating the work of others
- Experience with developing and deploying ML models in cloud environments e.g. Azure, AWS, and/or Google Cloud
- Expertise in healthcare data, e.g. medical and pharmacy claims, EMR/clinical data, lab data, etc.
- Experience with tools/libraries such as Github, Airflow, Streamlist etc.
- Experience with deploying ML models in Azure, AWS, and/or Google Cloud
- Experience with agile product development
- Collaborating with the team and working on code refactoring, cleaning data.
- Participation in community data science/ML activities such as hackathons, Kaggle, Stack Overflow and other such activities.
To apply for this job please visit careers.unitedhealthgroup.com.