Responsible for independently designing, building, and operating complex divisional data software and pipelines. Converts ambiguous business needs into scalable technical solutions, leads delivery of significant data product components, and raises engineering quality through sound architecture, testing, observability, and governance. Mentors less experienced engineers and coordinates effectively across technology and business teams.
Responsibilities
Leads technical discovery and translates complex divisional requirements into data architecture, interfaces, and delivery plans
Designs, builds, and operates scalable, secure, and resilient data ingestion, ELT, and integration services
Develops reusable frameworks, libraries, and patterns that improve engineering consistency and delivery speed
Designs dimensional and other fit-for-purpose data models; optimizes storage, query performance, and compute utilization
Establishes appropriate automated testing, data quality controls, monitoring, alerting, and recovery practices
Help shape and operationalize how Schwab uses data lineage to drive risk based decision making, working across business and technology teams to identify critical data flows, assess risk exposure, and translate insights into actionable roadmaps.
Compensation
In addition to the salary range, this role is also eligible for bonus or incentive opportunities.
Responsibilities
Shape and operationalize data lineage to drive risk-based decision making
Identify critical data flows and assess risk exposure across end-to-end lineages
Translate risk insights into clear prioritization signals and actionable roadmaps
Define and apply risk criteria and surface tradeoffs
Operationalize data risk metrics and indicators, monitoring trends and escalating emerging risks
The Business Analytics role supports multiple customer groups and/or therapeutic areas & will be an expert in statistical methodologies for measuring marketing impact.
Responsibilities
Conducting and interpretation of advance analytics to support decision making on promotional strategies and effectiveness (ROI and Marketing Mix analysis)
Supporting brand planning/field force evolution/non-personal digital/virtual activities and serving as inputs to the forecasting process
Conducts advanced analytics in support of brand planning and promotional resource allocation, resource allocation in customer channels including digital and evolution of commercial model
Liaises between Marketing and Sales in the development of business tactics and strategies
Responsible for executing departmental procedures and collaborating within the organization to ensure the marketing strategy is integrated into delivered sales force call plans for both in person and virtual / non-personal digital, telephone plans etc.
Requirements
Bachelor's degree
Master's degree
Nice to have: Analyzing large, deidentified patient claims data sets
Nice to have: Metabolic therapeutic areas such as CardioRenal Metabolic (e.g. Chronic Kidney and Hearth Failure)
Lead customer engagement and the design of a new financial ledger and lending backend as a Senior Product Owner with banking and lending expertise and an engineering background.
Compensation
Competitive compensation based on experience
Payment in U.S. dollars
Responsibilities
Be the day-to-day product contact for the customer: run workshops, gather requirements and manage expectations.
Own the backlog as Product Owner: write user stories and acceptance criteria, prioritize by value and risk, and accept delivered work.
Define and document the ledger and the lending backend, from origination to payoff, including business rules for interest, fees, payments and delinquency, with engineering and the customer's finance and operations teams.
Write requirements, data models, API specs and process flows that engineers can build from, and weigh architecture trade-offs with them.
Plan data migration and support user acceptance testing (UAT) with the customer.
Lead the development of pricing, credit-risk and portfolio-management solutions across Business and Commercial Banking, combining quantitative modelling with modern software-development practices.
Compensation
£95,418 to £106,020
Responsibilities
Own the methodology and lead the software implementation of Return on Risk Adjusted Capital models supporting the origination and pricing of commercial lending products.
Build production-quality solutions for loan pricing, portfolio management, capital allocation, forecasting and credit-risk analytics.
Develop reusable, well-documented and tested analytical code, applying version control, peer review and robust model-development standards.
Use Python, C#, and SQL to work with large datasets, automate analytical processes and improve the efficiency and control of existing tools.
Lead the application of advanced statistical and machine-learning techniques to identify growth opportunities, support client acquisition and deepen client relationships.
Requirements
Postgraduate qualification, or equivalent experience, in mathematics, statistics, physics, quantitative finance or another highly quantitative discipline
Responsible for the design, development, configuration, integration, enhancement, and lead operational support of the Workday platform.
Compensation
Expected base pay range for this role will be $92,500 - $125,000.
Responsibilities
Partner with business stakeholders, Workday module leads, internal IT teams, and external vendors to deliver scalable, secure, and high-quality Workday solutions.
Analyze business requirements and translate them into technical solutions, including configuration, workflow automation, integrations, testing, deployment, and production support.
Design, develop, and maintain Workday integrations, applications, and workflow automations across Core HCM, Payroll, Benefits, Recruiting, Compensation, Time Tracking, and other Workday modules.
Build and support integrations using Workday Studio, Core Connectors, EIB, Orchestrate, Raas, Extend, and SOAP/REST APIs.
Deliver technical solutions throughout the full lifecycle, including design, development, testing, deployment, documentation, and post-production support.
Requirements
Bachelor’s degree
Nice to have: Workday certifications in Integration, Studio, Orchestrate, Reporting, Extend
The Business Analyst will support data analysis and reporting for the Business Analytics team within Promoted Ads, Ticketmaster’s proprietary advertising platform, maintaining data accuracy, collaborating with Business Development, and coordinating data pipelines.
Compensation
The expected compensation for this position is: $75,000 – 85,000 USD.
Responsibilities
Maintain rigorous data hygiene across core performance reporting and financial accounting workflows
Write and troubleshoot SQL queries to pull, validate, and reconcile data across multiple sources
Serve as point of contact for Business Development, client representatives, and other commercial leaders for ad hoc client analytics needs
Translate data into clear commercial narratives, surfacing the “so what” behind trends for non-technical stakeholders
Liaise between Promoted Business Analytics and counterpart analytics teams to ensure data pipelines are properly ingested and distributed
Requirements
Bachelor's degree or equivalent practical experience
Hands-on AI leader passionate about building innovative solutions, developing technical talent, and transforming how financial services organizations leverage artificial intelligence.
Responsibilities
Lead the end-to-end delivery of AI use cases
Define the technical standards for AI delivery
Manage and mentor teams across data science, machine learning engineering, and operational business analytics
Serve as the primary translator between executive business goals and technical execution
Develop and execute the organization’s AI and analytics strategy
Requirements
Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, Data Science, Statistics, Applied Mathematics, Operations Research, Econometrics, or a closely related quantitative discipline
Nice to have: PhD in Computer Science, Machine Learning, Artificial Intelligence, Data Science, Statistics, Operations Research
Nice to have: Databricks Machine Learning Professional
Nice to have: Databricks Data Engineer Professional
Nice to have: Cloud Architect certification (Azure/AWS/GCP)
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