Data Scientist, Staff

Lyric, formerly ClaimsXten, is a leading healthcare technology company, committed to simplifying the business of care. Over 30 years of experience, dedicated teams, and top technology help deliver more than $14 billion of annual savings to our many loyal and valued customers—including 9 of the top 10 payers across the country. Lyric’s solutions leverage the power of machine learning, AI, and predictive analytics to empower health plan payers with pathways to increased accuracy and efficiency, while maximizing value and savings. Lyric’s strong relationships as a trusted ally to customers resulted in recognition from KLAS as “true partner” and “excellent value for investment,” with a top score for overall customer satisfaction and A+ likelihood to recommend in their October 2023 Payment Integrity and Accuracy Report. Discover more at Lyric.ai. 

Applicants must already be legally authorized to work in the U.S.  Visa sponsorship/sponsorship assumption and other immigration support are not available for this position.

The Staff Data Scientist plays a pivotal role in advancing our products and services by shaping solution design and supporting strategic decision-making. This individual collaborates closely with engineers, clinical experts, payment professionals, and business operations leaders to develop reporting and analyze large-scale healthcare claims and clinical datasets. By leveraging predictive modeling and AI algorithms, the Staff Data Scientist uncovers actionable insights that drive innovation and improve outcomes across the organization.

ESSENTIAL JOB RESPONSIBILITIES & KEY PERFORMANCE OUTCOMES

• Work cross functionally to identify opportunities for leveraging company data to drive business solutions.
• Mine and analyze data from claims databases to drive optimization and improvement of product development, sales, marketing techniques and business strategies.
• Assess the effectiveness and accuracy of new data sources and data gathering techniques.
• Develop custom data models and algorithms to apply to data sets.
• Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.
• Coordinate with different functional teams to implement models and monitor outcomes.
• Develop processes and tools to monitor and analyze model performance and data accuracy including responsible AI.

REQUIRED SKILLS & EXPERIENCE

• 5+ years experience manipulating data sets and building statistical models
• Advanced level SQL coding & query optimization
• Experience with healthcare data and standard UB/HCFA claim fields
• Experience with data in Snowflake on Cloud Platforms
• Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and generate insights from large data sets.
• Experience working with Java, Spark and/or Python
• Experience working in Project Management tools (Jira, Confluence)

• Strong problem-solving skills with an emphasis on product development.
• Excellent written and verbal communication skills for coordinating across teams
• Drive to learn and master new technologies and techniques
• Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
• Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
• Experience in analytic report and dashboard development

***The US base salary range for this full-time position is:

The specific salary offered to a candidate may be influenced by a variety of factors including but not limited to the candidate’s relevant experience, education, and work location. Please note that the compensation details listed in US role postings reflect the base salary only, and does not reflect the value of the total rewards compensation. ***

Lyric is an Equal Opportunity Employer that strives to create an inclusive environment, empower employees and embrace collaborative success.