Data Strategist

As a seasoned data strategist, you will utilize your expertise in marketing analytics and statistics to drive business decisions.

You will lead a team of professionals, working closely with stakeholders and clients to design, implement, and optimize advanced analytics solutions that solve complex business challenges.

• Team Leadership & Development:
  • Lead and mentor a team of professionals, 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 campaign optimization and customer segmentation.
  • Ensure robust model evaluation, validation, and deployment processes.
• Own the Analytics Charter:
  • Lead the development of end-to-end advanced analytics products, including predictive models and real-time dashboards.
  • Launch and manage experiments and proof-of-concept solutions to solve business challenges.
  • 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 data management processes for efficient ETL operations.
• 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.
  • Manage client expectations and ensure timely delivery of analytics projects.
• Cross-Functional Collaboration:
  • Work with cross-functional teams to integrate analytics 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, 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.
    • Experience in managing marketing analytics projects for international clients is mandatory.
    • Proven track record of managing analytics teams and delivering high-impact projects.
    • Prior experience in conceptualizing and scaling AI/ML PoCs or data product initiatives is a plus.
  • Technical Expertise:
    • Advanced proficiency in Python, SQL, and Statistical techniques.
    • Strong experience with machine learning techniques and frameworks (e.g., TensorFlow, Scikit-learn).
    • Expertise in data visualization tools (Power BI, Tableau).
    • Proficient in leveraging AI tools to enhance efficiency across analytics workflows and day-to-day deliverables.
    • Experience with cloud platforms like GCP (BigQuery).
    • Familiarity with data engineering practices and tools (e.g., Airflow, Snowflake) is an advantage.
  • Leadership & Collaboration:
    • Exceptional leadership skills with the ability to inspire and motivate teams.
    • Strong interpersonal skills to build effective relationships with stakeholders and clients.
    • Ability to manage multiple projects in a fast-paced, agile environment.
  • Strategic Thinking:
    • Deep understanding of marketing analytics concepts like campaign optimization and customer segmentation.
    • Ability to think critically and solve complex business problems with data-driven solutions.
  • 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.