ApplyDescription
The Data Scientist - Methods is a key member of the Product + Methods + Analytics (PMA) team at Springbuk. This role works closely with the product management team, our clinical expert and the engineering teams to design, test, implement and support complex analytic methodologies within the Springbuk product. They also closely collaborate with our client-facing teams and clients. The vision for Data Science is embedded across the Springbuk organization at many levels. Not only does this function work as a member of the PMA team to contribute directly to the maintenance and development of methodologies to be implemented in our software product for client use, but Data Science also plays a pivotal role in driving success across the organization.
The successful candidate will be passionate about discovering insights by applying sophisticated analytic techniques to Springbuk’s proprietary data (as well as other complex datasets). If this sounds like you, explore the job specifics below. You might be exactly who we’re looking for, and we’d love to get in touch!
Here’s what you will do:
- Support, maintain and enhance all Springbuk standard enrichments and methodologies including the Optum Symmetry suite (SRE, ETGs, ERGs and EBM)
- Develop a deep understanding of the Springbuk algorithms and calculations within each methodology and be able to clearly articulate both their business value
- Research and address internal and external (client) inquiries regarding existing methodologies and algorithms including detailed data investigation
- Lead Data Science efforts in creating state-of-the-art analytic capabilities to embed into the Springbuk product, working collaboratively with teams across Springbuk
- Formulate, research, prototype, and evaluate data science-based approaches to solving a given business challenge utilizing expertise in machine-learning, data mining, and information retrieval
- Proactively seek opportunities to apply data science skills that drive innovation throughout the organization
- Collaborate with Engineering teams to implement and deploy scalable solutions
- Collaborate to create solutions that reflect appropriate trade-offs between statistical precision, client value, and speed to market
- Develop a deep understanding of the business challenges for which we are solving
- Ensure the analytic integrity of Springbuk methods and algorithms by providing a data scientist perspective to their design, implementation and interpretation
- Provide clarification and/or analytic validation of Springbuk’s methods/algorithms to existing clients, prospects and/or internal stakeholders
- Create internal and client-facing documentation or presentations as needed to provide understanding of approaches, rationale for design decisions and appropriate interpretation of Springbuk methodologies
- Analyze client data to discern additional opportunities for methodology enhancements
- Support Sales and client-facing teams through industry and data subject matter expertise
Requirements
Requirements for a successful candidate:
- Deep understanding of the Optum Symmetry suite of methodologies including SRE, ETG, ERG and EBM
- BS in health informatics, computer science, statistics, data science, mathematics, operation research or related discipline
- Significant experience in data analysis, i.e., working with complex datasets using a variety of tools and techniques
- Knowledge of machine learning, statistics, optimization and/or related field
- P?assion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes
- Demonstrated success troubleshooting and analyzing complex data analytics challenges
- Solid understanding of employer-centered healthcare analytics, healthcare financial data, the nuances of working with claims data, episode groupers, predictive modeling concepts and other analytic methodologies
- Expertise with Python, SQL (ideally PostgreSQL and/or Snowflake)
- At least three years of experience working with healthcare claims data to support health plans, employers and/or brokers in analyzing population health
- Strong analytic and technical skills, with experience manipulating and analyzing large datasets and presenting clear and accurate results of analyses
- Self-motivation and the ability to work independently, along with a strong desire to collaborate, compromise, and communicate well within a small interdependent team structure
- Strong presentation and communication skills appropriate for audiences with a variety of levels of analytic expertise and knowledge
Not required but a preferred:
- Experience working for a healthcare data and analytics firm
- Experience with AWS (S3, RDS, Lambda, EC2)
- Ruby experience
- MS in computer science, statistics, data science, mathematics, operation research or related technical discipline
Here is how you will get ramped up for success:
30 Days:By the end of this period, you will be able to:
- Explain, at a high level, the business challenges that Springbuk aims to solve and the clients we serve
- Provide a high level overview of the Springbuk platform and the various components it contains
- Understand the Springbuk standard methodologies, algorithms and models (Optum ETGs, ERGs, Insights)
- Describe the various data-science based components within the Springbuk platform
Steps to get there:
- Participate in Springbuk platform demonstration
- Meet with all members of the Product team to gain an understanding of roles and responsibilities
- Meet with the SVP of Product to gain an understanding of Springbuk roadmap
- Meet with Chief Clinical Scientist to understand scope of responsibilities and knowledge transfer on current methodologies
- Meet with Engineering teams to gain an understanding of our architecture and data
- Review all analytical methodology documentation
60 Days:By the end of this period, you will be able to:
- Demonstrate a strong understanding of the analytic concepts and methodologies used at Springbuk
- Readily access Springbuk data, exhibit foundational knowledge of how to use sql database queries to access the data
- Readily access Springbuk data using Tableau to perform data analysis
- Have a basic understanding of the database contents, ingestion and storage process
- Begin to assist the PMA team with client questions related to methodologies
Steps to get there:
- Review all analytic methods documentation, including for algorithms that apply to various Insights and Answers, but also episodes, encounters, and gaps in care; where documentation does not exist, interview/meet with individuals with that knowledge
- Gain access to underlying Springbuk database through appropriate query tools and participate in any necessary knowledge sharing to become comfortable using those tools
- Gain access to Tableau and participate in any necessary knowledge sharing (formal or informal) on the Tableau tool, and specifically how to use it to access information in Springbuk database
- Meet with various Engineering team reps to receive an overview of data intake and QA process as well as the Springbuk database structure (tables, fields, etc.)
90 Days:By the end of this period, you will be able to:
- Support most internal and external questions regarding analytic methodologies (with limited support)
- Be comfortable describing all aspects of Springbuk product focusing on calculation and analytic methods
- Participate as an SME in Sales calls, client meetings, etc. lending industry knowledge and analytic credibility to Springbuk
- Utilize analytical skills and industry-awareness to guide development of new algorithms and data science models
- Apply data science expertise in the modification of existing algorithms, the development of new algorithms and data science models
Steps to get there:
- Participate in at least 2 sales meetings as a silent observer
- Present to members of your Springbuk team one of the Springbuk methodologies
Being You at Springbuk:
Springbuk’s goal is to attract and retain diverse talent and provide an inclusive environment for all where everyone’s voice is heard and all employees feel accepted. Springbuk is an equal opportunity employer and we do not discriminate on the basis of race, color, religion, creed, national origin or ancestry, ethnicity, sex (including pregnancy), gender (including gender nonconformity and status as a transgender or transsexual individual), age, physical or mental disability, citizenship, past, current or prospective service in the uniformed services, genetic information, or any other characteristic protected under applicable federal, state, or local law.
