Product Analyst

Key Responsibilities

Data Strategy Automation:

Lead data collection, processing, and quality assurance processes to ensure accuracy, completeness, and relevance.

Explore opportunities to incorporate generative AI models to automate and optimize processes, enhancing efficiencies in analytics, reporting, and decision-making.

Data Analysis Insight Generation:

Conduct in-depth analyses of user behaviour, campaign performance, and platform metrics to uncover insights that support crowdfunding success.

Translate complex data into clear, actionable insights that drive strategic decisions, providing stakeholders with the necessary information to enhance business outcomes.

Reporting Quality Assurance:

Design and maintain a robust reporting framework to deliver timely insights, enhancing data reliability and ensuring stakeholders are well-informed.

Monitor and improve data accuracy, consistency, and integrity across all data processes, identifying and addressing areas for enhancement.

Collaboration Strategic Planning:

Work closely with Business, Product, and IT teams to align data initiatives with Kettos objectives and growth strategy.

Propose data-driven strategies that leverage AI and automation to tackle business challenges and scale impact across the platform.

Mentor junior data scientists and analysts, fostering a culture of data-driven decision-making.

Required Skills and Qualifications

Technical Expertise:

Strong background in SQL, Statistics and Maths

Analytical Strategic Mindset:

Proven ability to derive meaningful, actionable insights from large data sets and translate findings into business strategies.

Experience with statistical analysis, advanced analytics

Communication Collaboration:

Exceptional written and verbal communication skills, capable of explaining complex data insights to non-technical stakeholders.

Strong interpersonal skills to work effectively with cross-functional teams, aligning data initiatives with organisational goals.

Preferred Experience:

Proven experience in advanced analytics roles

Experience leading data lifecycle management, model deployment, and quality assurance initiatives.