• Own the end-to-end program management of strategic initiatives for LiveRamp’s Data Marketplace, from initial scoping and requirements through launch and post-launch optimization, ensuring clear accountability, timelines, and success criteria. • Coordinate and communicate product and engineering work across multiple teams and stakeholders (Product, Engineering, Sales, Partnerships, Operations, and Support) so everyone is aligned on priorities, milestones, and risks. • Drive the software development lifecycle for marketplace programs, including ideation, specification, prioritization, design, implementation, testing, launch, and iteration, using data to guide tradeoffs and decisions. • Partner with Product Management to translate customer, partner, and internal stakeholder needs into actionable roadmaps, well-defined program plans, and clearly documented requirements. • Build and maintain program plans, dependency maps, and risk registers for complex, cross-functional efforts (such as new marketplace capabilities, large partner integrations, and platform migrations), and keep them current and visible. • Define, implement, and monitor program health metrics (for example, delivery predictability, cycle time, defect rates, adoption/usage, and operational SLAs) and use these to drive continuous improvement. • Facilitate effective Agile ceremonies and cross-team rituals (planning, backlog refinement, standups, demos, and retrospectives) to support predictable delivery and high team engagement. • Run cross-functional incident and issue response for marketplace-impacting problems: organize triage, coordinate short-term mitigation, and ensure follow-up actions and root-cause analysis are completed. • Identify process gaps and friction points in how marketplace work gets delivered (e.g., handoffs between teams, release processes, partner onboarding workflows) and lead structured efforts to improve or redesign them. • Create and maintain concise, executive-ready status reporting for your programs, highlighting progress, risks, decisions needed, and impact against goals. • Champion best practices in program and project management across the Data Marketplace and adjacent teams, helping to standardize tools, templates, and ways of working where it adds value. • Contribute to a culture of ownership, collaboration, and inclusion by modeling our values and supporting teams through ambiguity, changing priorities, and challenging timelines.

Role Description Join Amgen’s Mission of Serving Patients. In this role, you will design, build, and deploy scalable data products, dashboards, analytical models, and cloud-based data solutions that improve operational visibility, risk management, supplier performance monitoring, and business decision-making. This role will partner with External Supply stakeholders, internal manufacturing sites, contract manufacturing organizations, Supply Chain, Quality, Finance, and central information technology teams to translate business needs into trusted, actionable, and governed data solutions. The successful candidate will bring strong technical expertise in advanced analytics, data engineering, cloud data platforms, and data governance, along with working knowledge of pharmaceutical manufacturing, external supply, supply chain, finance, and procurement processes. - Design, build, and maintain data pipelines, curated datasets, analytical data products, and reporting layers using Python, SQL, and cloud-based data platforms. - Develop dashboards and visual analytics to monitor External Supply performance, manufacturing status, inventory, supply risk, supplier performance, procurement activity, and operational trends. - Apply statistical, analytical, and data science methods to identify patterns, generate insights, support scenario analysis, and improve business decision-making. - Partner with External Supply business stakeholders to define requirements, clarify business problems, identify data sources, and deliver fit-for-purpose digital and analytical solutions. - Integrate and analyze structured and non-structured data from enterprise systems, including ERP, supply planning, procurement, manufacturing, quality, finance, and external partner data sources. - Automate recurring reports and manual analyses to improve efficiency, consistency, and data accessibility. - Collaborate with information technology and business teams to design scalable, maintainable, and reusable data architecture. - Support data governance, data quality, documentation, and validation practices for analytics used in a regulated pharmaceutical environment. - Communicate analytical findings, technical recommendations, and business insights clearly to technical and non-technical audiences. - Promote best practices for code development, dashboard design, data management, analytics lifecycle management, and digital product sustainability. Qualifications - Doctorate degree - OR Master’s degree and 2 years of Data Scientist experience - OR Bachelor’s degree and 4 years of Data Scientist experience - OR Associate’s degree and 8 years of Data Scientist experience - OR High school diploma / GED and 10 years of Data Scientist experience Requirements - Experience in pharmaceutical, biotechnology, life sciences, or regulated manufacturing environments. - Strong proficiency in Python for data processing, automation, analytics, and model development. - Strong SQL skills, including complex queries, joins, aggregations, data transformation, and working with large datasets. - Experience developing dashboards or visual analytics using tools such as Tableau, Power BI, or similar platforms. - Experience with cloud databases or cloud data platforms such as Databricks, AWS, Azure, Google Cloud, or similar technologies. - Experience with data engineering processes, including ETL/ELT pipelines, data modeling, data integration, data quality, orchestration, and version control. - Experience designing scalable data models, reusable analytical datasets, and governed reporting layers. - Experience with cloud data platforms, data lake architectures, APIs, workflow orchestration tools, Git, and CI/CD concepts. - Ability to work cross-functionally with business stakeholders and technical teams to translate business requirements into analytical and digital solutions. - Knowledge of External Supply, contract manufacturing, pharmaceutical manufacturing, GMP operations, supplier management, material planning, or logistics processes. - Experience working with enterprise operation systems such as SAP, MES, LIMS, Veeva, procurement platforms, or external partner data sources. - Experience developing predictive analytics, forecasting models, optimization models, anomaly detection, machine learning solutions, or advanced statistical analyses. - Strong understanding of data governance, master data management, data lineage, documentation, and data quality practices. - Demonstrated ability to manage ambiguity, structure complex business problems, and deliver practical analytical solutions. - Strong communication, storytelling, and stakeholder engagement skills, with the ability to explain complex technical concepts to business audiences. - Ability to manage multiple priorities, work independently, and deliver high-quality results in a fast-paced, cross-functional environment. - Strong commitment to data integrity, compliance, scalability, and continuous improvement. Benefits - A comprehensive employee benefits package, including a Retirement and Savings Plan with generous company contributions, group medical, dental and vision coverage, life and disability insurance, and flexible spending accounts. - A discretionary annual bonus program, or for field sales representatives, a sales-based incentive plan. - Stock-based long-term incentives. - Award-winning time-off plans. - Flexible work models where possible. Salary Range The expected annual salary range for this role in the U.S. (excluding Puerto Rico) is 134,168.25 USD - 181,521.75 USD. Actual salary will vary based on several factors including but not limited to, relevant skills, experience, and qualifications.

Role Description Premier Enterprise Solutions is seeking an experienced Data Governance / Data Manager to support the Department of Veterans Affairs (VA) Office of Acquisition and Administration (OAA). This role is responsible for establishing and maturing enterprise data governance practices that support a Level 4–5 CMMI target operating maturity across the OAA application portfolio. The successful candidate will lead enterprise data governance initiatives by: - Identifying authoritative data sources - Standardizing data definitions - Improving metadata quality - Resolving data inconsistencies - Enhancing reporting accuracy across Microsoft-based platforms including SQL Server 2022, SSRS, Power BI, SharePoint, Power Apps, and Azure Data Engineering services This position will play a critical role in: - Improving data quality - Supporting audit readiness - Enabling enterprise-wide data-driven decision-making - Ensuring compliance with VA security, Authority to Operate (ATO), and governance requirements Qualifications - Bachelor's degree in Data Management, Information Systems, Computer Science, or a related field (no substitutions accepted) - Minimum 5 years of experience in: - Data Governance - Data Management - Data Administration - Experience implementing enterprise data governance frameworks and best practices - Strong knowledge of: - Microsoft SQL Server - Data quality management - Metadata management - Data lineage and traceability - Excellent analytical, documentation, and communication skills Requirements - Experience with: - Azure Data Engineering - SQL Server 2022 - Power BI - SharePoint - Microsoft Power Platform - SSRS - Experience supporting federal agencies, preferably the Department of Veterans Affairs - Knowledge of: - Master Data Management (MDM) - Data Fabric concepts - Metadata-driven architectures - CMMI maturity models - Authority to Operate (ATO) documentation - Experience supporting enterprise audit readiness and compliance initiatives Benefits - Paid vacation, sick leave, and holidays - Medical, dental, and vision insurance - Life insurance - Short- and long-term disability insurance - 401(k) retirement plan with company match and immediate vesting - Military leave - Professional training and development - Tuition reimbursement - Employee wellness program - And more

Role Description The Pricing Data Scientist is a hands-on, high-autonomy individual contributor responsible for owning end-to-end pricing analytics and measurement in close partnership with the Pricing organization. This role focuses on practical, decision-driven work including: - Competitive price validation - Pricing test measurement - Promotion and discount analysis - Elasticity assessment - Executive-ready insights The ideal candidate combines strong quantitative skills with pragmatic execution, is comfortable building and applying predictive models while working across SQL, Python, and analytics workflows, and can independently deliver results without heavy guidance. Success in this role requires judgment, a bias toward action, and the ability to clearly articulate the “so-what” behind the numbers. Job Expectations - Own end-to-end pricing analytics, modeling, and measurement in close partnership with the Pricing organization. - Build, validate, and maintain applied pricing models (e.g., elasticity, incrementality, sensitivity tiers). - Design and execute measurement approaches for pricing tests and promotions, including A/B tests and quasi-experimental methods. - Lead competitive pricing analytics, including validation of external pricing data and ongoing quality monitoring. - Translate complex analytical outputs into clear, decision-ready insights for pricing leadership and senior executives. - Partner closely with BI Analytics and Data Engineering to shape pricing datasets. - Independently develop analytical workflows using SQL and Python. - Contribute to the development of pricing dashboards and recurring analytical outputs for the Pricing team. - Continuously refine pricing measurement frameworks as the business evolves. - Experience deploying, monitoring, or operationalizing pricing or predictive models in a production analytics or ML environment. Qualifications - Strong applied quantitative background with demonstrated experience designing, building, and deploying Python-based data science models. - Hands-on expertise with SQL and Python, with the ability to independently extract, manipulate, model, and analyze large datasets. - Experience designing and interpreting pricing or promotional measurement, including experimentation (A/B testing). - Practical experience with pricing concepts such as elasticity, price sensitivity, discounting, promotions, and incrementality. - Proven ability to translate analytical outputs into clear, actionable insights. - Comfort operating with ambiguity and limited guidance. - Strong analytical problem-solving skills paired with business intuition. - Ability to collaborate effectively across Analytics, Pricing, Finance, and Engineering. Requirements - Typically requires ten (10) years of progressive experience in data science, analytics, or quantitative analysis roles. - Hands-on experience building and applying analytical or data science models. - Prior experience supporting pricing strategy, experimentation, or promotional measurement in fast-paced environments is strongly preferred. Education Requirements - Degree in Engineering, Math, Statistics, Finance, or Computer Science required. - Advanced degrees are welcome but not required. Compensation The expected salary range for this role is $175,000 - $198,000 USD. The actual base pay offered will be determined by factors such as the candidate's relevant experience, education, geographic location, and internal equity. Staffing Agency Submission Notice iHerb does not accept unsolicited 3rd party ("Agency") candidates. If you are an Agency, please send any requests to be considered as a supplier in our Vendor Management System to staffingvendors@iherb.com. Do not contact iHerb employees directly. Equal Opportunity Employer iHerb is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status.