Vacancy expired!
Blue Shield of California's mission is to ensure all Californians have access to high-quality health care at a sustainably affordable price. We are transforming health care in a way that truly serves our nonprofit mission by lowering costs, improving quality, and enhancing the member and physician experience.
To fulfill our mission, we must ensure a diverse, equitable, and inclusive environment where all employees can be their authentic selves and fully contribute to meet the needs of the multifaceted communities we serve. Our comprehensive approach to diversity, equity, and inclusion combines a focus on our people, processes, and systems with a deep commitment to promoting social justice and health equity through our products, business practices, and presence as a corporate citizen.Blue Shield has received awards and recognition for being a certified Great Place to Work, best place to work for LGBTQ equality, leading disability employer, one of the best companies for women to advance, Bay Area's top companies in volunteering & giving, and one of the world's most ethical companies. Here at Blue Shield of California, we are striving to make a positive change across our industry and the communities we live in - join us!Your RoleThe Advanced Analytics team develops and governs machine learning pipelines and applications supporting a wide array of use cases. We partner with business stakeholders to apply advanced techniques including text analytics of customer feedback data, complex modeling of clinical disease progression, and geospatial analysis of populations leveraging social determinants of health. The Data Scientist will report to the Director of Advanced Analytics . In this role, you will work with business stakeholders, data engineers, and other IT partners to ideate and build analytics-enabled solutions. You will perform research, inform design decisions, prototype data pipelines, build, deploy and govern models to monitor their impact .Your WorkIn this role, you will:- Collaborate with product owners and business stakeholders to identify opportunities to optimize processes and decision-making
- Perform data exploration using a combination of statistical programming languages (R, Python, SAS, Julia, Matlab, etc.) and visualization tools/frameworks (Tableau, D3, ggplot, matplotlib) to develop a deep understanding of the signal-to-noise ratio in the dataset
- Partner with the data engineering team to support rapid prototyping of training data set using a combination of tools and scripting languages (SQL, Apache Spark, etc.)
- Perform simple to complex feature engineering routines using the appropriate techniques for the given data and business problem (statistical transformations, encoding categorical variables, time series decomposition, TF-IDF, etc.)
- Develop robust and reproducible model validation procedures to handle the bias-variance trade-offs, and generate the appropriate range of model performance metrics for evaluation and monitoring (AUC, precision, recall, R-squared, etc.)
- Perform model validation and implement appropriate procedures to promote transparency and safeguard against algorithmic bias.
- Deploy models for multiple consumption patterns and monitor for model drift.
- Requires a bachelor's degree in mathematics, statistics, computer science or equivalent quantitative scientific discipline
- Requires at least 3 years of professional Data Science or ML experience; or a Ph.D degree in operations research, applied statistics, data mining, machine learning, or other quantitative discipline
- Requires high proficiency in Python, R, SAS, Julia or equivalent statistical programming language
- Requires high proficiency in scalable data transformation techniques using SQL, Spark or equivalent
- Experience working with data in relational databases, massively parallel processing platforms, NoSQL databases, and big data platforms preferred
- Requires proficiency with version control and CI/CD tools
- Proficiency demonstrating reproducible model flow and outputs using Jupyter, RMarkdown, or equivalent format preferred
- Honest. We hold ourselves to the highest ethical and integrity standards. We build trust by doing what we say we're going to do and by acknowledging and correcting where we fall short
- Human. We strive to be our authentic selves, listening and communicating effectively, and showing empathy towards others by walking in their shoes
- Courageous. We stand up for what we believe in and are committed to the hard work necessary to achieve our ambitious goals
Vacancy expired!