{"schemaVersion":"jobsearcher.job.v1","id":"043eaeb42ed07b2d0d6f29b1","url":"https://jobsearcher.com/jobs/043eaeb42ed07b2d0d6f29b1","canonicalUrl":"https://jobsearcher.com/jobs/043eaeb42ed07b2d0d6f29b1","title":"Data Scientist","description":"Job Description: Data Scientist – AI Enabled Call Center Efficiency and CEX\nLocation- Hybrid, Jersey City, NJ\nSalary- $70- $115k plus bonus\nFor more information on benefits and what we offer please visit us at https://www.exlservice.com/us-careers-and-benefits\nThe posted range is the hiring range for this role — a subset of the broader range available to employees over time — and reflects base salary across our national hiring scale. Final offers are based on several factors, including the candidate's skills and experience, internal pay equity, work location, market conditions for the role, and the specific scope and responsibilities of the position. The top of the range is reserved for candidates who notably exceed the requirements; the lower end applies to those with less experience or fewer preferred qualifications. For positions based in higher-cost zones (e.g., California, New York, New Jersey), actual compensation may exceed the posted range; your recruiter will share specifics during the process.\n\nWe are seeking a highly motivated Sr. Data Scientist to lead end-to-end Next Best Action (NBA) strategy, delivery, and optimization initiatives. This role combines advanced analytics, business problem-solving, campaign decisioning, and operational ownership to drive personalized member engagement across lines of business.\nThe ideal candidate will be equally comfortable with analytics and execution, owning the full NBA lifecycle—from strategy translation and targeting logic to deployment, measurement, and continuous optimization.\nSuccess Profile\nThe successful candidate will demonstrate:\nStrong business problem-solving capabilities alongside technical expertise.\nOwnership mentality for both analytics delivery and campaign operations.\nAbility to balance modeling and AI-driven insights (approximately 50%) with execution, delivery ownership, and NBA operations (approximately 50%) .\nExcellent stakeholder communication and cross-functional collaboration skills.\n\nResponsibilities: Key Responsibilities\nOwn the complete NBA delivery lifecycle, including strategy, design, development, testing, deployment, measurement, and ongoing optimization.\nTranslate business objectives into actionable inclusion/exclusion criteria, targeting logic, and decision strategies.\nDevelop and maintain SQL/BigQuery-based data pipelines supporting campaign targeting, sizing, execution, and reporting.\nBuild and enhance measurement frameworks to evaluate campaign effectiveness, business outcomes, and member engagement.\nPerform ad hoc analyses to identify optimization opportunities and support stakeholder decision-making.\nConfigure and support NBA implementations within Pega , including launch readiness and process validation.\nConduct campaign QA, operational monitoring, and issue resolution to ensure successful NBA execution.\nPartner with business, product, and technology teams to drive data-informed decisioning and recommendation strategies.\nSupport experimentation and test-and-learn initiatives, including A/B testing and performance measurement.\nLeverage predictive models, AI/ML, and LLM-based inference capabilities where appropriate to improve decisioning effectiveness.\n\nQualifications: Required Qualifications\nBachelor's or Master's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, or a related quantitative field.\nAdvanced proficiency in:\nSQL\nGoogle Cloud Platform (GCP)\nBigQuery\nPython\nHands-on experience developing and managing BigQuery pipelines and analytical workflows.\nStrong understanding of campaign targeting, audience segmentation, recommendation systems, and decision strategies.\nExperience designing and implementing measurement frameworks and performance analytics.\nAbility to translate complex business problems into scalable analytical solutions.\nPreferred Qualifications\nExperience in healthcare analytics, member engagement, or payer organizations.\nKnowledge of experimentation methodologies, uplift modeling, ranking/recommendation systems, and product analytics.\nExposure to machine learning and Generative AI/LLM inference use cases.\nExperience supporting operational campaign delivery and production decisioning environments.\nExperience with Pega Decisioning or related campaign orchestration platforms.\nStrong experience in Next Best Action (NBA) , campaign management, decisioning, or customer engagement analytics.","company":"Ex","rawCompany":"ex","city":"Dallas","state":"TX","isRemote":false,"isActive":false,"createdAt":"2026-08-04T22:49:23.540Z","occupations":[{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-2051.01","title":"Business Intelligence Analysts","slug":"business-intelligence-analysts"}],"industries":[{"code":"541690","title":"Other Scientific and Technical Consulting Services","slug":"other-scientific-and-technical-consulting-services"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541990","title":"All Other Professional, Scientific, and Technical Services","slug":"all-other-professional-scientific-and-technical-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Data Scientist","description":"Job Description: Data Scientist – AI Enabled Call Center Efficiency and CEX\nLocation- Hybrid, Jersey City, NJ\nSalary- $70- $115k plus bonus\nFor more information on benefits and what we offer please visit us at https://www.exlservice.com/us-careers-and-benefits\nThe posted range is the hiring range for this role — a subset of the broader range available to employees over time — and reflects base salary across our national hiring scale. Final offers are based on several factors, including the candidate's skills and experience, internal pay equity, work location, market conditions for the role, and the specific scope and responsibilities of the position. The top of the range is reserved for candidates who notably exceed the requirements; the lower end applies to those with less experience or fewer preferred qualifications. For positions based in higher-cost zones (e.g., California, New York, New Jersey), actual compensation may exceed the posted range; your recruiter will share specifics during the process.\n\nWe are seeking a highly motivated Sr. Data Scientist to lead end-to-end Next Best Action (NBA) strategy, delivery, and optimization initiatives. This role combines advanced analytics, business problem-solving, campaign decisioning, and operational ownership to drive personalized member engagement across lines of business.\nThe ideal candidate will be equally comfortable with analytics and execution, owning the full NBA lifecycle—from strategy translation and targeting logic to deployment, measurement, and continuous optimization.\nSuccess Profile\nThe successful candidate will demonstrate:\nStrong business problem-solving capabilities alongside technical expertise.\nOwnership mentality for both analytics delivery and campaign operations.\nAbility to balance modeling and AI-driven insights (approximately 50%) with execution, delivery ownership, and NBA operations (approximately 50%) .\nExcellent stakeholder communication and cross-functional collaboration skills.\n\nResponsibilities: Key Responsibilities\nOwn the complete NBA delivery lifecycle, including strategy, design, development, testing, deployment, measurement, and ongoing optimization.\nTranslate business objectives into actionable inclusion/exclusion criteria, targeting logic, and decision strategies.\nDevelop and maintain SQL/BigQuery-based data pipelines supporting campaign targeting, sizing, execution, and reporting.\nBuild and enhance measurement frameworks to evaluate campaign effectiveness, business outcomes, and member engagement.\nPerform ad hoc analyses to identify optimization opportunities and support stakeholder decision-making.\nConfigure and support NBA implementations within Pega , including launch readiness and process validation.\nConduct campaign QA, operational monitoring, and issue resolution to ensure successful NBA execution.\nPartner with business, product, and technology teams to drive data-informed decisioning and recommendation strategies.\nSupport experimentation and test-and-learn initiatives, including A/B testing and performance measurement.\nLeverage predictive models, AI/ML, and LLM-based inference capabilities where appropriate to improve decisioning effectiveness.\n\nQualifications: Required Qualifications\nBachelor's or Master's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, or a related quantitative field.\nAdvanced proficiency in:\nSQL\nGoogle Cloud Platform (GCP)\nBigQuery\nPython\nHands-on experience developing and managing BigQuery pipelines and analytical workflows.\nStrong understanding of campaign targeting, audience segmentation, recommendation systems, and decision strategies.\nExperience designing and implementing measurement frameworks and performance analytics.\nAbility to translate complex business problems into scalable analytical solutions.\nPreferred Qualifications\nExperience in healthcare analytics, member engagement, or payer organizations.\nKnowledge of experimentation methodologies, uplift modeling, ranking/recommendation systems, and product analytics.\nExposure to machine learning and Generative AI/LLM inference use cases.\nExperience supporting operational campaign delivery and production decisioning environments.\nExperience with Pega Decisioning or related campaign orchestration platforms.\nStrong experience in Next Best Action (NBA) , campaign management, decisioning, or customer engagement analytics.","datePosted":"2026-08-04T22:49:23.540Z","dateModified":"2026-08-04T22:49:23.540Z","hiringOrganization":{"@type":"Organization","name":"Ex","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Dallas","addressRegion":"TX","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"043eaeb42ed07b2d0d6f29b1"},"url":"https://jobsearcher.com/jobs/043eaeb42ed07b2d0d6f29b1"}}