Lead data science initiatives for Pharmacy Benefit Manager (PBM) operations, driving efficiency and growth through advanced analytics, predictive modeling, and generative AI.
Compensation
$79,310.00 - $173,040.00
Responsibilities
Design, build, and validate data science solutions including generative AI pipelines and predictive models
Manage end-to-end delivery from data extraction to production deployment and monitoring
Extract, curate, and analyze large-scale operational data using SQL and Python
Translate complex modeling outputs into clear business narratives for clinical and business leadership
Requirements
Bachelor's degree in Computer Science, Statistics, Mathematics, Analytics, Engineering, or related quantitative field
Master's degree in a quantitative field or MBA preferred
Support EDPR’s global fleet of generating assets by detecting, reporting, and documenting potential future failures in wind turbines, solar panels, BESS, and other electric systems using condition monitoring and data analytics.
Responsibilities
Detect potential failures using EDPR’s corporate condition monitoring tools to analyze operational data
Communicate clear inspection and repair recommendations to the site managers and technicians
Communicate each finding to the site personnel using the EPDR tools
Provide remote support to site personnel to ensure recommendations are addressed correctly and within the appropriate time
Report the results of the inspection feedback and relay decisions of replacing/repairing the component, material, system, etc.
Requirements
Bachelor’s degree in engineering (Mechanical or a related field)
Master’s preferred
Nice to have: Familiarity with planetary gearboxes, generators, solar, BESS, and/or power generation and conversion equipment
Nice to have: Familiarity with rotating equipment reliability and lubrication
Own core backend infrastructure that processes complex clinical and financial workflows, helping bring new capabilities into reliable production systems.
Compensation
Base salary: $160,000 to $200,000 annually. Visa sponsorship is not available.
Responsibilities
Build and scale distributed backend systems for chart processing, claims, authorizations, denials, and payer and provider integrations
Develop browser and computer-use automation to navigate medical record software and payer portals
Design reliable systems to process scanned charts, PDFs, structured claims, unstructured notes, and operational data at scale
Build orchestration, queuing, retry, and observability infrastructure for long-running workflows across healthcare systems
Partner with research and product engineers to put clinical intelligence capabilities into production and establish engineering patterns
Requirements
Degree in computer science, mathematics, or a related field
Analyze, design, code and test multiple components of application code across one or more clients, perform maintenance, enhancements and/or development work, and lead process improvements.
Responsibilities
Analyze client requirements and design effective solutions
Code and test multiple components of application software
Perform maintenance and enhancements to existing applications
Collaborate with multiple teams and stakeholders
Lead efforts to identify and implement process improvements
Develop insights using a wide range of data sources, design and implement solutions, deploy well-tested, maintainable solutions into live systems, develop tools and infrastructure for sensor data analysis, collaborate closely with engineers, product managers, and domain experts to translate business needs into technical impact
Compensation
Competitive salary (85.000 - 100.000 EUR p.a. depending on seniority/exoerience)
Responsibilities
Develop insights using a wide range of data sources
Design and implement solutions
Deploy well-tested, maintainable solutions into live systems
Develop tools and infrastructure for sensor data analysis
Collaborate closely with engineers, product managers, and domain experts
Requirements
Bachelor's or higher degree in Mathematics, Statistics, Computer Science, Engineering, or a related field
Applied Scientist focused on developing and optimizing language model-powered conversational experiences for Alexa for Shopping.
Responsibilities
Develop and maintain LLM agents, including automated evaluation pipelines, LLM-as-a-judge methodologies, rubric design, and dataset curation.
Experiment with techniques such as retrieval augmentation, context enrichment, prompt decomposition, and model fine-tuning or post-training strategies.
Lead post-training of small language models to deliver low-latency conversational and shopping experiences.
Apply applied machine learning and deep learning techniques to improve ranking, relevance, personalization, and multimodal understanding.
Design and evaluate agentic architectures that balance diverse shopping use cases.
Requirements
Master's degree or above in computer science, machine learning, engineering, or related fields
Nice to have: PhD in computer science, machine learning, engineering, or related fields
Nice to have: Machine Learning and Large Language Model fundamentals
Architect and build a brand-new growth engine: an event-driven platform that ingests customer signals from across our ecosystem to power intelligent decision-making across all customer touchpoints.
Responsibilities
Architect, build, and scale backend services that ingest and unify customer data from multiple sources into actionable signals for personalization, recommendations, and lifecycle journeys
Design the decision engines and business logic that orchestrate outreach across communication channels, integrating experimentation frameworks and machine learning models
Partner with product, data, and machine learning colleagues to turn customer insight into features people actually use
Own your services end to end, from code quality and performance to reliability after launch
Spot gaps in how we serve customers and drive the fix yourself
Lead the development and implementation of advanced data science models and algorithms to improve dispute resolution and operational effectiveness.
Compensation
The base pay for this role will depend on where you work and the relevant experience and expertise you bring. The expected range of pay for this role by location is: San Jose, CA | Salary: $190,112.00-300,500.00 per annum. 40 hours per week; M-F, 9:00 a.m. to 5:00 p.m.
Responsibilities
Develop, optimize, and execute data-driven strategies to identify, analyze, and manage payment disputes and chargebacks
Leverage large datasets to improve dispute resolution outcomes
Work cross-functionally with fraud prevention, customer service, and compliance teams
Analyze large volumes of transaction, dispute, and chargeback data
Develop and optimize dispute strategies
Requirements
Master’s degree in Data Science, Statistics, Business Analytics, or a closely related field
Bachelor’s degree in Data Science, Statistics, Business Analytics, or a closely related field
Support the development of advanced analytical solutions that identify aberrant provider billing and utilization patterns in Medicare and Medicaid programs.
Compensation
We offer competitive compensation with opportunities for bonuses, employer paid health care, training and development funds, and 401k match.
Responsibilities
Gather and define data requirements and resolve data-related challenges in collaboration with client and project teams.
Develop and refine data models to identify vulnerabilities, anomalous activity, and potential risks within Medicare and Medicaid programs.
Analyze provider billing and utilization patterns using large healthcare claims datasets.
Consult and advise on data analysis, statistical modeling, and analytical techniques.
Research and evaluate new modeling methods, tools, market trends, and proven approaches.
Requirements
Bachelor’s or Master’s degree in Data Analytics, Statistics, Health Policy, Public Health, or a related field
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