• Lead the design, development, and deployment of scalable machine learning solutions focused on pricing optimization, demand forecasting, and promotion planning. • Build and improve statistical and machine learning models for: - Demand forecasting - Price elasticity modeling - Promotion optimization - Inventory and revenue forecasting • Design, build and deploy robust ML pipelines in Databricks, build model monitoring systems, and production-ready APIs. • Ability to design and evaluate transformer-based time series forecasting models for large-scale retail sales forecasting and demand planning. • Drive experimentation, model evaluation, and continuous improvement of forecasting and pricing models. • Analyze large-scale structured and unstructured retail datasets to uncover trends, customer behavior patterns, and pricing insights. • Develop data-driven strategies that help maximize revenue, profitability, and pricing efficiency across products and categories. • Apply advanced statistical techniques and machine learning algorithms to solve complex retail business problems. • Collaborate closely with Product, Engineering, Data Engineering, and Business teams to translate business requirements into scalable ML solutions. • Mentor junior data scientists and provide technical guidance across cross-functional teams. • Communicate analytical findings and business recommendations clearly to both technical and non-technical stakeholders.

• 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