Nevada Staffing
Data Management & Strategy - Life Sciences - Senior Manager- Consulting - Locati
Nevada Staffing, Las Vegas, Nevada, us, 89105
Technology - Data Management & Strategy Senior Manager Life Sciences Sector
At EY, we'll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world. We are seeking an experienced forecasting leader with over 10+ years of experience who is passionate about all things commercial pharma. This role is focused on strategic forecasting and allied capabilities and hence candidate should have deep expertise in commercial analytics, strategic/financial forecasting and preferably demand planning/supply chain forecasting. Areas of expertise needed in strategic planning, forecasting & benchmarking, market & gap analysis, financial reporting, market entry strategy, commercial analytics & brand development. As a Senior Manager in Data Management & Strategy, you will lead the charge in technology transformation projects, aligning with strategic objectives to drive desired outcomes. You'll be the assurance to leadership, managing timelines, costs, and quality standards, while steering both technical and non-technical teams to deliver top-notch technology solutions and infrastructure. You will guide clients through the evolving world of analytics, data governance, and modern data platforms. We'll rely on you to provide strategic leadership and a unique business perspective on how data and analytics can improve operations, increase agility, and drive transformation. In this role, you will design and apply comprehensive methods and practices to govern the entire lifecycle of data assets, ensuring their protection and monetization. You will perform maturity assessments on data management capabilities and advise on tools and roadmaps to implement them, all while aligning data strategies with business objectives. This is a high-growth, high-visibility role with significant opportunity to shape digital and data strategies across the oil & gas sector. Your key responsibilities include leading complex processes and projects, ensuring quality and risk management while navigating organizational dynamics. This role offers a unique opportunity to work closely with clients, providing insights and solutions that drive business value. You will be responsible for managing client relationships and engagement delivery, with regular travel requirements to meet client needs. In this pivotal role, you will: Exercise judgment in selecting methods and techniques for obtaining results. Define and execute the analytics and data governance strategy for oil & gas clients, aligning with business objectives and regulatory requirements. Develop and implement robust data governance frameworks, including policies, data stewardship models, roles, and accountability across the organization. Oversee the delivery of technology projects, ensuring adherence to methodologies like Agile and Waterfall, and mentoring team members. Drive continuous improvement and innovation, applying research, analysis, and best practices to advance processes and solutions. Manage complex technical initiatives, providing expert guidance, resolving issues, and achieving performance objectives across client service, risk management, and team development. Engage actively with clients, leading workstreams, and identifying opportunities to expand services. Spearhead RFP responses and manage engagement economics, including resource planning and budgeting. Travel as required to meet client needs and project demands. Overall delivery: Lead delivery of large client engagements be accountable for success of the delivery with very high quality and timeliness in an evolving business environment. Develop resource plans and budgets for engagements, ensuring effective engagement economics. Strong functional knowledge in brand volume forecasts for both short-term and long-term strategic and operational planning. Solve regional and brand-level analytical challenges using quantitative approaches. Deep understanding of forecasting algorithms (time series forecasting, patient flow), external datasets (e.g. IQVIA, Kantar, Komodo) Manage project budgets, timelines, and resources to ensure successful project delivery. Advise team on performing sensitivity analyses to identify opportunities and manage risks, enhancing forecast accuracy. Strong digital engineering, data science and/or data engineering experience working with life science clients Strong knowledge of AI technologies and frameworks Working experience with industry leading methods of delivery for digital, data and analytic products Help set and execute governance for engagements including performance scorecards, RACI, manage risk/mitigation etc. Practice development: Serve as a part of a leadership team at EY focusing on all things customer in pharma and helping build the practice to achieve future vision and goals. Contribute actively to points-of-view, POCs, proposals and selling materials to help win and close deals across horizontals and use cases. Identify opportunities where EY can push frontiers for pharma clients in the customer space. Stay up to date with the latest pharma trends and evaluate state-of-the-art technologies/framework to drive innovation. Identify and develop new business opportunities within the life sciences domain. Stakeholder management: Foster strong relationships with clients, acting as a trusted advisor and advocate for their success. Collaborate with clients and stakeholders to translate business asks to scalable, operable solutions. Team and People Development: Provide leadership and development for direct reports. Recruit, develop, and retain a strategic and operationally capable workforce skilled and knowledgeable in pharma. Effectively manage an agile organization that continuously meets the needs of a changing portfolio. Build an organizational culture that fosters inclusion and innovation. Create an environment that fosters professional and career development. In partnership with line management, develop the team's expertise in pharma, therapeutic area science, strategic thinking, project management, and leadership. Develop and mentor junior team members, fostering a culture of continuous learning and growth. Put together development plan for team members and help plan career growth and opportunities for other team members. Evaluate and manage performance for leaders and other team members. Skills and attributes for success: Proven ability to construct and direct technology projects in line with organizational goals. Expertise in project and program delivery methodologies, with the ability to mentor others. Strong analytical skills to develop creative solutions for complex problems. Leadership skills to manage professional staff and supervise teams effectively. Strategic thinking to drive sales, business growth, and client satisfaction. Experience: 8+ years of experience in python programming specializing in data handling, managing, ETL jobs. 8+ years of hands-on experience in querying data in cloud platforms such s AWS, Azure etc. 8+ years of experience in building statistical forecast models for pharma industry. Exposure to sourcing/automating data pulls using APIs from different platforms e.g. evaluate pharma, pricecentriq. 8+ Years of experience in leading report development and design. Pharma forecast data exposure preferred. E.g. Exposure to IQVIA MIDAS, KANTAR, GLOBOCAN. Understanding of Concepts and Metrics in forecasting funnel. E.g. Incidence, prevalence other Epi metrics, Units, patients, dosage, Line of therapy etc. Skillsets: Visualization Tools: Power BI, Spotfire, Power Apps. Data Manipulation & Analysis: SQL, Excel. Programming Languages: Python. Data Sources: Familiarity with relational databases, data lakes, and clinical trial data systems. Cloud Platforms: AWS (S3, EC2, Lambda), Azure (Data Lake, Azure Functions). Programming Languages: Python (Dash, Pandas, NumPy), SQL. DevOps Tools: Jenkins, Git, GitHub (good to have). Database Technologies: MySQL, PostgreSQL, NoSQL databases. Certification in AWS Solutions Architect / Microsoft Azure Data Engineer (good to have). Statistical Programming Languages: Python, R. Libraries & Frameworks: Pandas, NumPy, Scikit-learn, StatsModels, Tidyverse, caret. Data Manipulation Tools: SQL, Excel. Data Visualization Tools: Matplotlib, Seaborn, ggplot2. Machine Learning Techniques: Supervised and unsupervised learning, model evaluation (cross-validation, ROC curves). To qualify for the role, you must have: A bachelor's degree required; Master's degree preferred in a quantitative or technical field (e.g., statistics, computer science, engineering, mathematics) with prior consulting experience required. 8 years+ of relevant experience in delivering client engagements across sizes and geographies with deep expertise in Pharma commercial industry.
At EY, we'll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world. We are seeking an experienced forecasting leader with over 10+ years of experience who is passionate about all things commercial pharma. This role is focused on strategic forecasting and allied capabilities and hence candidate should have deep expertise in commercial analytics, strategic/financial forecasting and preferably demand planning/supply chain forecasting. Areas of expertise needed in strategic planning, forecasting & benchmarking, market & gap analysis, financial reporting, market entry strategy, commercial analytics & brand development. As a Senior Manager in Data Management & Strategy, you will lead the charge in technology transformation projects, aligning with strategic objectives to drive desired outcomes. You'll be the assurance to leadership, managing timelines, costs, and quality standards, while steering both technical and non-technical teams to deliver top-notch technology solutions and infrastructure. You will guide clients through the evolving world of analytics, data governance, and modern data platforms. We'll rely on you to provide strategic leadership and a unique business perspective on how data and analytics can improve operations, increase agility, and drive transformation. In this role, you will design and apply comprehensive methods and practices to govern the entire lifecycle of data assets, ensuring their protection and monetization. You will perform maturity assessments on data management capabilities and advise on tools and roadmaps to implement them, all while aligning data strategies with business objectives. This is a high-growth, high-visibility role with significant opportunity to shape digital and data strategies across the oil & gas sector. Your key responsibilities include leading complex processes and projects, ensuring quality and risk management while navigating organizational dynamics. This role offers a unique opportunity to work closely with clients, providing insights and solutions that drive business value. You will be responsible for managing client relationships and engagement delivery, with regular travel requirements to meet client needs. In this pivotal role, you will: Exercise judgment in selecting methods and techniques for obtaining results. Define and execute the analytics and data governance strategy for oil & gas clients, aligning with business objectives and regulatory requirements. Develop and implement robust data governance frameworks, including policies, data stewardship models, roles, and accountability across the organization. Oversee the delivery of technology projects, ensuring adherence to methodologies like Agile and Waterfall, and mentoring team members. Drive continuous improvement and innovation, applying research, analysis, and best practices to advance processes and solutions. Manage complex technical initiatives, providing expert guidance, resolving issues, and achieving performance objectives across client service, risk management, and team development. Engage actively with clients, leading workstreams, and identifying opportunities to expand services. Spearhead RFP responses and manage engagement economics, including resource planning and budgeting. Travel as required to meet client needs and project demands. Overall delivery: Lead delivery of large client engagements be accountable for success of the delivery with very high quality and timeliness in an evolving business environment. Develop resource plans and budgets for engagements, ensuring effective engagement economics. Strong functional knowledge in brand volume forecasts for both short-term and long-term strategic and operational planning. Solve regional and brand-level analytical challenges using quantitative approaches. Deep understanding of forecasting algorithms (time series forecasting, patient flow), external datasets (e.g. IQVIA, Kantar, Komodo) Manage project budgets, timelines, and resources to ensure successful project delivery. Advise team on performing sensitivity analyses to identify opportunities and manage risks, enhancing forecast accuracy. Strong digital engineering, data science and/or data engineering experience working with life science clients Strong knowledge of AI technologies and frameworks Working experience with industry leading methods of delivery for digital, data and analytic products Help set and execute governance for engagements including performance scorecards, RACI, manage risk/mitigation etc. Practice development: Serve as a part of a leadership team at EY focusing on all things customer in pharma and helping build the practice to achieve future vision and goals. Contribute actively to points-of-view, POCs, proposals and selling materials to help win and close deals across horizontals and use cases. Identify opportunities where EY can push frontiers for pharma clients in the customer space. Stay up to date with the latest pharma trends and evaluate state-of-the-art technologies/framework to drive innovation. Identify and develop new business opportunities within the life sciences domain. Stakeholder management: Foster strong relationships with clients, acting as a trusted advisor and advocate for their success. Collaborate with clients and stakeholders to translate business asks to scalable, operable solutions. Team and People Development: Provide leadership and development for direct reports. Recruit, develop, and retain a strategic and operationally capable workforce skilled and knowledgeable in pharma. Effectively manage an agile organization that continuously meets the needs of a changing portfolio. Build an organizational culture that fosters inclusion and innovation. Create an environment that fosters professional and career development. In partnership with line management, develop the team's expertise in pharma, therapeutic area science, strategic thinking, project management, and leadership. Develop and mentor junior team members, fostering a culture of continuous learning and growth. Put together development plan for team members and help plan career growth and opportunities for other team members. Evaluate and manage performance for leaders and other team members. Skills and attributes for success: Proven ability to construct and direct technology projects in line with organizational goals. Expertise in project and program delivery methodologies, with the ability to mentor others. Strong analytical skills to develop creative solutions for complex problems. Leadership skills to manage professional staff and supervise teams effectively. Strategic thinking to drive sales, business growth, and client satisfaction. Experience: 8+ years of experience in python programming specializing in data handling, managing, ETL jobs. 8+ years of hands-on experience in querying data in cloud platforms such s AWS, Azure etc. 8+ years of experience in building statistical forecast models for pharma industry. Exposure to sourcing/automating data pulls using APIs from different platforms e.g. evaluate pharma, pricecentriq. 8+ Years of experience in leading report development and design. Pharma forecast data exposure preferred. E.g. Exposure to IQVIA MIDAS, KANTAR, GLOBOCAN. Understanding of Concepts and Metrics in forecasting funnel. E.g. Incidence, prevalence other Epi metrics, Units, patients, dosage, Line of therapy etc. Skillsets: Visualization Tools: Power BI, Spotfire, Power Apps. Data Manipulation & Analysis: SQL, Excel. Programming Languages: Python. Data Sources: Familiarity with relational databases, data lakes, and clinical trial data systems. Cloud Platforms: AWS (S3, EC2, Lambda), Azure (Data Lake, Azure Functions). Programming Languages: Python (Dash, Pandas, NumPy), SQL. DevOps Tools: Jenkins, Git, GitHub (good to have). Database Technologies: MySQL, PostgreSQL, NoSQL databases. Certification in AWS Solutions Architect / Microsoft Azure Data Engineer (good to have). Statistical Programming Languages: Python, R. Libraries & Frameworks: Pandas, NumPy, Scikit-learn, StatsModels, Tidyverse, caret. Data Manipulation Tools: SQL, Excel. Data Visualization Tools: Matplotlib, Seaborn, ggplot2. Machine Learning Techniques: Supervised and unsupervised learning, model evaluation (cross-validation, ROC curves). To qualify for the role, you must have: A bachelor's degree required; Master's degree preferred in a quantitative or technical field (e.g., statistics, computer science, engineering, mathematics) with prior consulting experience required. 8 years+ of relevant experience in delivering client engagements across sizes and geographies with deep expertise in Pharma commercial industry.