Decision Science Manager

As part of our Cinemark Universe, you'll discover fun opportunities with real growth potential and plenty of perks. With 500+ theatres and nearly 6,000 screens; we're truly a global presence of 20,000 movie lovers working together to make unforgettable experiences.

• →Lead end-to-end problem solving for strategic and operational business challenges across the enterprise.

• →Translate ambiguous business questions into analytical frameworks, hypotheses, and actionable recommendations.

• →Apply statistical analysis, predictive modeling, machine learning, optimization, simulation, forecasting, and causal inference to improve decision-making.

• →Design experiments, A/B tests, and measurement frameworks to validate initiatives and quantify business impact.

• →Build scalable models, dashboards, and decision-support tools that help teams act with confidence.

• →Partner with cross-functional leaders to identify opportunities, evaluate tradeoffs, and support execution.

• →Leverage customer, operational, financial, and market data to uncover insights that inform enterprise decisions.

• →Mentor analysts and data scientists in analytical rigor, technical problem-solving, and business application.

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• Bachelor’s degree in computer science, Engineering, a quantitative field, technical discipline, or business-related field; master’s degree preferred.

• 7+ years of experience in decision science, data science, analytics, strategy, consulting, or a related field.

• Proven track record of solving complex business problems and driving measurable results.

• Strong proficiency in SQL, Python, statistical modeling, predictive modeling, and analytical methodologies.

• Experience building dashboards and data visualizations in Power BI, including working with high-cardinality data.

• Familiarity with Microsoft Azure, Microsoft Fabric, and modern data platforms.

• Strong business acumen, stakeholder management, executive storytelling, and communication skills.

• Ability to clearly explain analytical approaches, model assumptions, results, and implications to technical and non-technical stakeholders.

• Strong attention to detail and ability to manage multiple competing priorities in a fast-paced environment.