
Data Analyst Leader
2 days ago
As a Data Analytics Strategist, you will drive business growth by leveraging your analytical expertise to design and implement data-driven solutions. You will lead a team of analysts, working closely with cross-functional teams and clients to develop advanced analytics strategies that meet complex business challenges.
- Team Leadership & Development:
Lead and mentor a team of analysts, fostering a culture of collaboration and innovation.
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 (MMM), uplift modeling, incrementality studies, customer segmentation, lifetime value modeling, and real-time optimization.
Ensure robust model evaluation, validation, and deployment processes.
- 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.
Requirements and Skills- Experience:
5+ years of professional experience in analytics, data science, or related roles.
At least 3 years' experience in the digital marketing industry is mandatory.
Proven track record of managing analytics teams and delivering high-impact projects.
- Technical Expertise:
Advanced proficiency in Python, SQL, and Statistical techniques.
Strong experience with machine learning techniques and frameworks.
Expertise in data visualization tools.
- Leadership & Collaboration:
Exceptional leadership skills with the ability to inspire and motivate teams.
Strong interpersonal skills to build effective relationships with stakeholders and clients.
- Communication:
Excellent written and verbal communication skills with the ability to present complex data insights to non-technical audiences.
Experience in preparing executive-level reports and presentations.
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