Cambia Health Solutions: Data Science Engineer
Seeking a Data Engineer to design, develop, and implement end-to-end cloud based machine learning production pipelines with high availability for a wide variety of health related projects.
Cambia Health Solutions is working to create a seamless and frictionless health care experience for consumers nationwide. This presents a unique challenge and opportunity for innovative solutions.
Our Data Science Engineers design, develop, and implement end-to-end cloud based machine learning production pipelines (data exploration, sampling, training data generation, feature engineering, model building, and performance evaluation) with high availability for a wide variety of health related projects with opportunity to improve health quality of millions. You should be passionate about finding insights in data, comfortable with large and fragmented data sets, and command a variety of analytic tools at your disposal.
In addition to quantitative mastery, the ideal candidate will effectively interpret and communicate strategic results to varied audiences, and provide analytic support for companywide process and operational improvement efforts. The ideal candidate is an independent, solution-oriented thinker with a strong Computer Science background, full stack software engineering skills, practical experience in machine learning and real world experience in building end to end data science.
Responsibilities & Requirements:
Minimum Requirements, Competencies and Knowledge
For all levels:
- Whole-brain thinking: Possessing the ability to think creatively and demonstrate analytical skills, analyzing complex situations both alone and as part of a team, learning quickly and synthesizing solutions, options and action plans.
- Solid data structures & algorithms background.
- Mastery of one of Python, Java, C++, Scala or equivalent language.
- Experience with cleaning, aggregating, and pre-processing data from varied sources.
- Experience creating complex SQL queries for standard as well as ad hoc data mining purposes.
- Demonstrated experience operating in a Unix/Linux environment.
- Excellent problem solving, critical thinking, and communication skills.
- Strong ability to evaluate and adopt new technologies in a short time.
- Coursework or practical experience with machine learning, data mining, and constructing analytical models and algorithms.
- Demonstrated ability to work with minimal direction, with the ability to coordinate complex activities.
Additional Minimum Requirements for Data Science Engineer II:
- Demonstrated experience with providing advanced data insights in an e-commerce, internet advertising or related field.
- Solid experience in full software development lifecycle.
- Strong competencies in platform/backend service technologies, data structures, software design, and profiling.
- Strong proficiency writing production-quality code, preferably industry engineering experience with machine learning projects (e.g. recommendation, ranking, optimization).
- Demonstrated proficiency in Relational databases and NoSQL databases.
- Demonstrated proficiency in Hadoop, Spark, Storm or related paradigms and associated languages such as Pig, Hive, Mahout.
- Experience in AWS, Azure, Google Cloud or other cloud ecosystems.
- Experience in Information Retrieval technologies: Elasticsearch, Solr, or Lucene.
- Experience in Agile software development process, Test-Driven development and Continuous Integration.
- Demonstrated experience performing data extraction and transformation to construct modeling and evaluation datasets.
- Demonstrated knowledge of and practical experience applying data mining methodologies and building algorithms.
- Demonstrated analytical skills, with the ability to analyze complex situations, learn quickly and synthesize corresponding solutions, options and action plans.
Additional Minimum Requirements for Data Science Engineer Senior:
- Industry experience and proficiency in competencies listed above for Data Science Engineer II.
- Industry engineering experience with machine learning projects (e.g. recommendation, ranking, optimization).
- Deep understanding of and experience with machine learning models and data analysis.
- Experience in building data science platforms.
- Experience in building online experiment frameworks.
- Significant experience developing and maintaining production services and libraries (preferably in cloud environments), including strong knowledge of algorithms and data structures.
- Ability to coordinate cross-functionally to drive solutions and resolve issues in a timely and effective manner.
- Demonstrated understanding of the principles of rigorous code review.
Normally to be proficient in the competencies listed above:
Data Science Engineer I would have a bachelor’s degree in Computer Science or related field and 3 years of related work experience or equivalent combination of education and experience. Master’s or PhD degree preferred.
Data Science Engineer II would have a bachelor’s or Master’s in Computer Science or related field and 6 years of related work experience or equivalent combination of education and experience. Master’s or PhD degree preferred.
Data Science Engineer Senior would have a Masters or PhD degree in Computer Science or related field and 8 years of database analytics experience or equivalent combination of education and experience. PhD degree preferred.
General Functions & Outcomes:
For all levels (Note that these responsibilities are representative but not complete). Higher level roles involve successively stronger degrees of initiative taking and innovation beyond the core responsibilities listed here):
- Design and develop end-to-end cloud based machine learning production pipelines (data exploration, sampling, training data generation, feature engineering, model building, and performance evaluation) with high availability for a wide variety of health related projects with opportunity to improve health quality of millions.
- Building automated & enhanced Data Science stack management with model update/testing (regression, shadow, parallel, A/B) capabilities
- Build frameworks for experience capture and feed into training data
- Develop the core Data Science services with near real-time capabilities: Fetch, Search, Predictor.
- Design, build, and deploy platforms, services, abstractions, and frameworks that allow the Data Scientists to conceive of, develop, and deploy their ideas with autonomy.
- Build and maintain tools which allow Data Scientists to perform their own ETL tasks.
- Execute continuous integration, continuous deployment, and DevOps best practices
- Work with large volumes of both structured and unstructured data
- Produce documentation for code, APIs, and procedures
- Collect, measure, and interpret process performance data; using tools such as Pareto charts, flow charts, process maps, Cause and Effect diagrams, scatter plots, histograms, and control charts.
- Troubleshoot and triage problem reports, resolve, and escalate as required
- Ensure the appropriate identification of root causes through effective use of data analysis tools and techniques.
Additional General Functions & Outcomes for Level II:
- Perform responsibilities above with an increased degree of independence and self-direction.
- Provide higher level consultation on data findings and recommendations.
- Works and interacts across the organization with a variety of business units.
- Develop and implement scalable and efficient modeling algorithms that can work with large-scale data in production systems
- Develop distributed learning algorithms for classification and regression
- Establish critical foundational information extraction and retrieval capabilities
Additional General Functions & Outcomes for Senior:
- Perform responsibilities above with an increased degree of independence and self-direction. Take initiative to pursue larger-scope projects.
- Design, and implement online experiments frameworks, including A/A and A/B testing, in a variety of configuration environments.
- Devise creative solutions for building highly scalable distributed production systems for both internal and external customers.
- Provide architectural input and review of services and APIs for data ingest and dispersal within the ecosystem
- Provides higher level analysis and data interpretation in support of strategy development, program implementation and analysis.
- Create influential metrics, dashboards, and presentations that use information to influence senior leadership on business trends and strategies.
- Acts as a data and analytics subject matter expert on cross-functional teams brought together to work toward the development and execution of strategic initiatives.
- Responsible for developing new data solutions for the enterprise, building statistical models.
- Work primarily performed in an office environment.
- Travel may be required, locally or out of state.
- May be required to work overtime and outside of normal hours.
At Cambia, we advocate for transforming the health care system. You aren’t satisfied with the status quo and neither are we. We're looking for individuals who are as passionate as we are about transforming the way people experience health care. We offer a competitive salary and a generous benefits package. We are an equal opportunity employer dedicated to workforce diversity and a drug and tobacco-free workplace. All qualified applicants will receive consideration for employment without regard to race, color, national origin, religion, age, sex, sexual orientation, gender identity, disability, protected veteran status or any other status protected by law. A drug screen and background check is required.
Cambia’s portfolio of companies spans health care information technology and software development; retail health care; health insurance plans that carry the Blue Cross and Blue Shield brands; pharmacy benefit management; life, disability, dental, vision and other lines of protection; alternative solutions to health care access; and free-standing health and wellness solutions. We have nearly a century of experience in developing and providing health solutions to serve our members. We had our beginnings in the logging communities of the Pacific Northwest as innovators in helping workers afford health care. That pioneering spirit has kept us at the forefront as we build new avenues to improve access to and quality of health care for the future.