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Senior Manager Analytics Jobs (Remote work)

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Senior Sap Analytics & Data Management Consultant
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Join WE ARE META as a Senior SAP Analytics & Data Management Consultant. This remote role in Portugal requires 7+ years of expertise in SAP platforms (BW, SAC, Datasphere), HANA modelling, and data governance. Lead projects, mentor teams, and enjoy career growth, health insurance, and a meal card...
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Portugal
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Not provided
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We Are Meta
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Until further notice
Senior Analytics Manager
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Lead analytics strategy and execution at a scaling global tech company. Manage a team, build foundational processes, and drive impact across product, marketing, and business domains. Enjoy remote work, health insurance, learning credits, and annual company retreats.
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Airalo
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Until further notice
Senior Analytics Manager
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Lead our data-driven strategy as a Senior Analytics Manager. You will manage a team and apply expertise in Marketing Measurement, Product Analytics, and Business Analytics. This remote role requires EU residency and experience in MTA, MMM, A/B testing, and executive reporting. Drive insights that...
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Airalo
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Until further notice
Senior GTM Operations & Analytics Manager
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Seeking a Senior GTM Operations & Analytics Manager to join our RevOps team. You will build scalable analytics frameworks, derive actionable insights, and optimize processes to drive global marketing and sales performance. This builder/operator role requires 5+ years in Revenue Operations, advanc...
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United States
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116000.00 - 174000.00 USD / Year
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Matillion
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Until further notice
A Senior Manager Analytics role is a pivotal leadership position at the intersection of data science, business strategy, and people management. Professionals in these jobs are responsible for transforming raw data into a strategic asset, guiding their organizations with actionable insights that drive growth, efficiency, and competitive advantage. They act as the crucial bridge between technical data teams and executive leadership, ensuring that analytics initiatives are closely aligned with core business objectives. Typically, a Senior Manager Analytics oversees the entire analytics lifecycle. This involves leading a team of data scientists, analysts, and BI specialists to design, develop, and deploy advanced analytical solutions. Common responsibilities include defining the analytics roadmap, prioritizing projects based on business impact, and establishing robust governance frameworks for model development and deployment. They are accountable for the end-to-end delivery of insights, from data preprocessing and model training to the communication of findings and monitoring of outcomes in production. A significant part of the role is stakeholder management: collaborating with department heads, category teams, or operational leaders to identify key problems, frame business questions in analytical terms, and champion data-driven decision-making at the highest levels. The skill set required for these leadership jobs is both deep and broad. Technically, a strong foundation in statistical methods, machine learning algorithms, and data engineering principles is essential. Proficiency in programming languages like Python and SQL, along with experience with cloud platforms (AWS, Azure, GCP) and data visualization tools (Tableau, Power BI), is standard. Beyond technical acumen, exceptional leadership and communication skills are non-negotiable. Senior Managers must recruit, mentor, and develop high-performing teams, fostering a culture of innovation and continuous learning. They must possess a sharp commercial mindset to translate complex analytical outputs into clear, compelling business recommendations for non-technical audiences. Strategic thinking, project management expertise, and the ability to manage multiple priorities in a dynamic environment are critical hallmarks of success in these roles. Ultimately, Senior Manager Analytics jobs are for those who are not just experts in data, but in leveraging data to tell a story, influence strategy, and deliver measurable business value. They are strategic partners who ensure that their organization doesn't just collect data, but uses it intelligently to forecast trends, optimize operations, mitigate risks, and uncover new opportunities for growth.

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