Senior 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.

Generative AI & Predictive Modeling:

Leverage generative AI and machine learning to build, train, and deploy predictive models, including user behavior prediction, donor engagement, and campaign success rates.

Develop and implement automated models and solutions using generative AI to enhance engagement, optimize workflows, and improve platform 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.

Technical Expertise:

Strong background in SQL, Python, and/or R, with hands-on experience in data science and machine learning.

Advanced knowledge of generative AI models and tools and experience implementing automation solutions with these technologies.

Proficiency with machine learning techniques such as k-Nearest Neighbors, Naive Bayes, SVM, and Decision Forests, with the ability to implement and optimize these models in production.

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, and predictive modeling.

Communication & Collaboration:

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

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

Preferred Experience:

Proven experience in data science, AI, or advanced analytics roles, ideally within the technology or social impact sectors.

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