Senior Data Strategist

13 hours ago

Solapur, Maharashtra, India beBeeAnalytics Full time US$ 1,30,000 - US$ 1,65,000
Lead Data Strategist

As a senior data strategist, you will leverage your extensive experience in marketing, analytics, statistics, and machine learning to drive business outcomes through data-driven strategies.

This role involves leading a team of analysts, working closely with cross-functional teams and clients to design, implement, and optimize advanced analytics solutions that solve complex business challenges.

Key ResponsibilitiesTeam Leadership & Development:
  • Lead and mentor a team of analysts, fostering a culture of collaboration, innovation, and excellence.
  • Provide training and guidance on analytics best practices, tools, and methodologies.
  • Ensure alignment of team goals with organizational objectives.
Strategic Analytics Planning:
  • Collaborate with stakeholders to understand business objectives and design data-driven solutions.
  • Translate complex business problems into actionable analytical frameworks.
Advanced Marketing Analytics & Modeling:
  • Develop and oversee the implementation of predictive models, machine learning algorithms, and statistical analyses to solve business problems.
  • Champion advanced analytics use cases, such as market mix modeling, uplift modeling, incrementality studies, customer segmentation, lifetime value modeling, and real-time optimization.
  • Ensure robust model evaluation, validation, and deployment processes.
Analytics Vision & Roadmap:
  • Lead the development of end-to-end advanced analytics products, including predictive models, real-time dashboards, and proof-of-concept (PoC) solutions to solve marketing challenges.
  • Launch and manage experiments and PoCs across key areas like campaign optimization, media planning, budget optimization, and customer analytics.
  • Drive the vision for analytics capabilities, integrating them into the company's strategic roadmap.
Data Governance & Quality Assurance:
  • Oversee data integrity, accuracy, and consistency across all analytics projects.
  • Establish data governance policies and ensure compliance with data security standards.
  • Streamline ETL processes for efficient data management.
Client Engagement & Delivery:
  • Act as a strategic advisor to clients, providing insights and recommendations based on advanced analytics.
  • Oversee the creation of compelling data visualizations and dashboards tailored to client needs.
Cross-Functional Collaboration:
  • Work with marketing, product, and engineering teams to integrate analytics and AI solutions into decision-making processes and products.
  • Drive alignment between analytics initiatives and broader business strategies.
Innovation & Continuous Improvement:
  • Stay abreast of emerging trends in analytics, data science, machine learning, and ad-tech to identify new opportunities.
  • Encourage a culture of experimentation, leveraging cutting-edge tools and techniques.

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