Alabama Staffing
Data Management & Strategy - Life Sciences - Senior Manager- Cons...
Alabama Staffing - Birmingham, Alabama, United States, 35275
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Overview
Technology - Data Management & Strategy Senior Manager Life Sciences Sector
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 include 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: 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 includes: Leading delivery of large client engagements, being accountable for success with high quality and timeliness in an evolving business environment. Developing 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. Solving 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). Managing project budgets, timelines, and resources to ensure successful project delivery. Advising 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. Helping set and execute governance for engagements including performance scorecards, RACI, manage risk/mitigation, etc. Practice development includes: Serving 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. Contributing actively to points-of-view, POCs, proposals, and selling materials to help win and close deals across horizontals and use cases. Identifying opportunities where EY can push frontiers for pharma clients in the customer space. Staying up to date with the latest pharma trends and evaluating state-of-the-art technologies/frameworks to drive innovation. Identifying and developing new business opportunities within the life sciences domain. Stakeholder management includes: Fostering strong relationships with clients, acting as a trusted advisor and advocate for their success. Collaborating with clients and stakeholders to translate business asks to scalable, operable solutions. Team and people development includes: Providing leadership and development for direct reports. Recruiting, developing, and retaining a strategic and operationally capable workforce skilled and knowledgeable in pharma. Effectively managing an agile organization that continuously meets the needs of a changing portfolio. Building an organizational culture that fosters inclusion and innovation. Creating an environment that fosters professional and career development. In partnership with line management, developing the teams expertise in pharma, therapeutic area science, strategic thinking, project management, and leadership. Developing and mentoring junior team members, fostering a culture of continuous learning and growth. Putting together development plans for team members and helping plan career growth and opportunities for other team members. Evaluating and managing performance for leaders and other team members. To excel in this role, you will need: 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 as AWS, Azure, etc. 8+ years of experience in building statistical forecast models for the 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 the 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 the Pharma commercial industry.
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 include 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: 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 includes: Leading delivery of large client engagements, being accountable for success with high quality and timeliness in an evolving business environment. Developing 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. Solving 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). Managing project budgets, timelines, and resources to ensure successful project delivery. Advising 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. Helping set and execute governance for engagements including performance scorecards, RACI, manage risk/mitigation, etc. Practice development includes: Serving 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. Contributing actively to points-of-view, POCs, proposals, and selling materials to help win and close deals across horizontals and use cases. Identifying opportunities where EY can push frontiers for pharma clients in the customer space. Staying up to date with the latest pharma trends and evaluating state-of-the-art technologies/frameworks to drive innovation. Identifying and developing new business opportunities within the life sciences domain. Stakeholder management includes: Fostering strong relationships with clients, acting as a trusted advisor and advocate for their success. Collaborating with clients and stakeholders to translate business asks to scalable, operable solutions. Team and people development includes: Providing leadership and development for direct reports. Recruiting, developing, and retaining a strategic and operationally capable workforce skilled and knowledgeable in pharma. Effectively managing an agile organization that continuously meets the needs of a changing portfolio. Building an organizational culture that fosters inclusion and innovation. Creating an environment that fosters professional and career development. In partnership with line management, developing the teams expertise in pharma, therapeutic area science, strategic thinking, project management, and leadership. Developing and mentoring junior team members, fostering a culture of continuous learning and growth. Putting together development plans for team members and helping plan career growth and opportunities for other team members. Evaluating and managing performance for leaders and other team members. To excel in this role, you will need: 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 as AWS, Azure, etc. 8+ years of experience in building statistical forecast models for the 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 the 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 the Pharma commercial industry.