Job Description
<h3>📋 Description</h3> • Lead the research, discovery, and full-cycle development of machine learning solutions, including model development, deployment, maintenance, and performance evaluation, ensuring seamless integration into production environments for the Cint Exchange.
• Develop a comprehensive, predictive understanding of marketplace dynamics, including price elasticity, supply/demand balance, and their underlying mechanics within the Cint Exchange, providing deep analytical insights.
• Independently and confidently carry out complex project planning, development, and maintenance end-to-end with minimal supervision.
• Analyze large, diverse datasets to extract impactful insights that can guide Exchange product and pricing strategy.
• Collaborate with cross-functional teams (Product, Engineering, Commercial, Operations, Finance) to design, implement, and test new and existing products, as well as to understand, analyze, explain, and predict the impact of platform algorithms on clients and partners.
• Define, establish, and drive the development of advanced statistical and machine learning methods, setting modeling standards and best practices.
• Conduct exploratory analyses to deepen insights into key metrics and trends, and lead the design and execution of A/B tests and other complex experiments to validate hypotheses for the Exchange.
• Continuously evaluate and validate both internal and external products to ensure Cint's continued success and the health of the Exchange.
• Create clear, effective deliverables that communicate complex insights and recommendations through compelling visualizations and presentations tailored to diverse technical and non-technical audiences. <h3>🎯 Requirements</h3> • Minimum 5 years of solid working experience in a Data Science capacity, with demonstrated experience in leading projects or initiatives.
• A Master's degree (or equivalent) in Statistics, Quantitative Sciences, Data Science, Operations Research, or a related quantitative field.
• Strong ability to manipulate, analyze, and interpret large, complex datasets independently.
• Deep understanding of advanced statistical techniques and concepts (e.g., properties of distributions, hypothesis testing, parametric/non-parametric tests, survey design, sampling theory, experimental design, including multivariate testing, regression/predictive modeling, causal inference, and A/B testing).
• Strong knowledge of various machine learning techniques (e.g., clustering, regression, decision trees, neural networks, etc.) and their real-world advantages and drawbacks.
• Proven experience applying statistical and modeling techniques to solve complex business problems in real-world scenarios.
• Proficiency in Python (for statistical and ML package tools).
• Proficiency in SQL and working with large-scale databases.
• Comfortable researching and adopting new methods, tools, and techniques, and able to mentor junior colleagues on their application. <h3>🏖️ Benefits</h3> • We deliver across borders.
• Innovation is in our blood.
• We’re pioneers in our industry.
• We bring the best ideas to life.
• We’re accountable for our work and actions.
• We’re open, honest and kind, always.
• We learn from each other’s experiences.
• Every opinion matters.
• We embrace diversity, equity and inclusion.