Senior Data Scientist

At Quest Analytics, the models and insights our Data Science team delivers help solve real problems around the accuracy, adequacy, and accessibility of healthcare provider networks. We're looking for a Senior Data Scientist to join our team. In this role, you'll leverage complex healthcare data to drive insights, improve data quality, and enable product innovation. You'll develop scalable machine learning models and AI-driven approaches to solve high-impact business problems for health plan networks, and help shape how Quest Analytics continues to evolve its data science capabilities. This is a senior individual contributor role with significant opportunity to influence our products, technical approaches, and data strategy, including how Quest Analytics uses machine learning, advanced analytics, and emerging AI technologies. If you're someone who likes digging into complicated datasets, challenging assumptions, experimenting with new approaches, and ultimately turning that work into scalable solutions, we'd love to talk with you. What You'll Do You'll partner across Data, Product, Engineering, and Client teams to: Design, develop, optimize, and scale machine learning models and advanced analytics solutions to improve provider data quality and generate meaningful network insightsApply statistical modeling, predictive analytics, and machine learning techniques (classification, regression, clustering, NLP, anomaly detection) to solve business problemsResearch open-ended healthcare and provider-data challenges, form hypotheses, and develop action plans and analytical approaches to turn findings into actionable solutionsDevelop novel algorithms to solve complex or unprecedented problemsEvaluate and improve existing models and algorithms to increase accuracy, performance, scalability, and reliability, and measure the resulting business impactPerform large-scale data processing and analysis using Python, SQL, Databricks, Spark, and distributed computing across structured and unstructured datasetsDevelop and maintain automated systems for anomaly detection, data validation, feature engineering, and continuous model monitoringDesign feature engineering strategies and evaluate model performance using appropriate validation techniquesEvaluate and integrate third-party data sources, tools, and vendors to strengthen our datasets and analytical capabilitiesPartner with Engineering to productionize models and build scalable, reliable solutions within our software productsApply LLM tools such as Claude to accelerate analysis, automate workflows, and improve documentation, and explore opportunities in generative AI, NLP, and AI agentsDevelop and maintain metrics to evaluate model performance, data quality, and business impactTranslate complex findings into clear, actionable insights for technical and non-technical stakeholdersPresent findings and recommendations to Network Analytics leadership and broader company audiencesPartner with Product and business teams to identify opportunities for new features, metrics, and data-driven solutionsMentor other data scientists and analysts, and contribute to technical standards, data governance, and MLOps best practicesParticipate in cross-functional initiatives and support client-facing analytics discussions as needed What You'll Need 7+ years of experience in data science, machine learning, or advanced analytics, preferably in a SaaS organizationMaster's degree in Data Science, Computer Science, Statistics, Mathematics, or a related discipline, or equivalent relevant experienceDemonstrated experience building and delivering machine learning models into productionAdvanced Python skills, including tools such as pandas, NumPy, and scikit-learnStrong experience with Databricks, Spark, or comparable distributed computing technologiesAdvanced SQL skillsExperience with ML frameworks such as TensorFlow, PyTorch, or similar technologiesStrong understanding of machine learning techniques including classification, regression, clustering, NLP, and anomaly detectionStrong applied statistics knowledge, including hypothesis testing, regression analysis, and probabilityExperience working with large, messy, and complex datasetsUnderstanding of MLOps, including deployment, monitoring, validation, and model lifecycle managementExperience using LLMs and AI-assisted tools to improve data science workflowsAbility to independently tackle ambiguous problems and determine an effective path forwardAbility to explain complex technical findings in a way that creates clear business valueStrong collaboration skills and experience working across Product, Engineering, Data, and business stakeholdersExperience leading technical initiatives and mentoring others Experience in one or more of these areas would be especially valuable: Healthcare provider data, provider networks, or healthcare analyticsHealthcare, SaaS, or another highly regulated data environmentIntegrating ML models into production software productsData quality, entity resolution, anomaly detection, or large-scale data validationGenerative AI, NLP, LLM applications, or agentic workflowsData visualization and communicating analytical results to clients or executive audiences About Quest Analytics For more than 20 years, we’ve been improving provider network management one groundbreaking innovation at a time. 90% of America’s health plans use our tools, including the eight largest in the nation. Achieve your personal quest to build a great career here. What You’ll Appreciate Workplace flexibility – you choose between remote, hybrid or in-officeAffordable employee medical, dental and vision plans with low employee cost401k MatchingWellness benefitsCompetitive salary and success sharing bonusFlexible vacation, plus sick time and holidaysAn entrepreneurial culture that won’t limit you to a job descriptionBeing listened to, valued, appreciated -- and having your contributions rewardedEnjoying your work each day with a great group of people Apply TODAY! careers.questanalytics.com Next Steps After you apply, you will receive an email confirming receipt of your application. If your background and experience align with our needs, a member of the Quest Analytics Talent Acquisition team will contact you regarding next steps in the process. Candidates will receive communication throughout the interview process regarding their status and progression. Interview Process The interview process may vary by role but typically includes: Recruiter Video InterviewVideo Interview with the Hiring ManagerTeam and/or Panel Interview(s)Role-Specific Assessment, Presentation, or Case Study (if applicable)Professional Reference Checks via Skill SurveyFinal Interview with Executive Leadership Video Camera Usage Policy Quest Analytics is a remote-first organization that values collaboration, communication, and engagement. To support a connected and productive work environment, candidates are expected to participate in all virtual interviews with their cameras enabled. Video participation helps create a more interactive interview experience, allows for stronger communication and relationship-building, and supports our commitment to maintaining a secure hiring process. Camera usage also serves as an important safeguard against fraudulent applicants, identity misrepresentation, unauthorized participation, and other security risks that have become increasingly common in remote hiring environments. Candidates who are unable or unwilling to participate on camera during the interview process may not be considered for employment. Relocation Requirement While many positions at Quest Analytics are remote, employees are expected to reside in and perform work from the location disclosed during the hiring process. Any relocation must be communicated to and approved by Quest Analytics in advance. This policy helps ensure compliance with employment and tax regulations, protects company and client data, and reduces risks associated with unauthorized work arrangements and employment misrepresentation. AI Tools As part of our hiring process, Quest Analytics may use AI-assisted tools to help screen applications and support interview documentation, including resume-matching software and AI-generated interview summaries. These tools inform but do not replace human judgment; all hiring decisions are made by Quest Analytics team members. If you have questions about our use of AI in hiring, please contact [email protected] . Visa sponsorship is not available at this time. Preferred work locations are within one of the following states: Alabama, Arizona, Arkansas, Colorado, Connecticut, Delaware, Florida, Georgia, Idaho, Illinois, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maine, Maryland, Massachusetts, Michigan, Minnesota, Mississippi, Missouri, Montana, Nebraska, Nevada, New Hampshire, New Mexico, North Carolina, North Dakota, Ohio, Oklahoma, Oregon, South Carolina, South Dakota, Tennessee, Texas, Utah, Vermont, Virginia, West Virginia, Wisconsin, or Wyoming. Quest Analytics provides equal employment opportunities to all people without regard to race, color, religion, sex, national origin, ancestry, marital status, veteran status, age, disability, sexual orientation or gender identity or expression or any other legally protected category. We are committed to creating and maintaining a workforce environment that is free from any form of discriminations or harassment. Applicants must be legally authorized to work in the United States. Verification of employment eligibility will be required at the time of hire. Persons with disabilities who anticipate needing accommodations for any part of the application process may contact, in confidence [email protected] NOTE: Staffing agencies, headhunters, recruiters, and/or placement agencies, please do not contact our hiring managers directly. We are not currently working with additional outside agencies at this time. Any job posting displayed on websites other than questanalytics.com or jobs.lever.co/questanalytics/ may be out of date, inaccurate and unavailable RECRUITMENT FRAUD ALERT We understand that some individuals have recently been impersonating recruiters from Quest Analytics® and soliciting fake job opportunities. We urge you not to disclose any personal or financial information to them. We use only our official website ( https://questanalytics.com ), email domain (@questanalytics.com), and verified social media accounts to communicate with candidates. If you suspect fraudulent behavior, please report it to us at [email protected] . We appreciate your interest in working with us. To learn more: https://questanalytics.com/news/recruitment-fraud-alert/ We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.