Lead Data Scientist

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Signature Aviation

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

🏨 Hospitality

📦 Logistics

✈️ Travel

Hospitality • Logistics • Travel

Signature Aviation is the world’s largest network of private aviation terminals, providing exceptional experiences and essential support to business and private aviation customers. With a presence in over 200 locations across 27 countries on five continents, Signature Aviation offers world-class services including sustainable aviation fuel, custom sales solutions, maintenance, and real estate. As a leading hospitality company within the aviation industry, it ensures a seamless travel experience for customers globally.

📋 Description

• Design, develop, and implement statistical, machine learning, forecasting, optimization, and predictive models • Apply regression, classification, clustering, time series analysis, anomaly detection, and other quantitative methods • Translate business challenges into scalable analytical solutions generating measurable business outcomes • Conduct exploratory data analysis to identify trends, patterns, opportunities, and risks • Assess data quality, completeness, and suitability for analytical and modeling initiatives • Design, develop, and validate features to improve model performance and business relevance • Lead the full lifecycle of data science solutions from problem definition and model development through deployment and ongoing optimization • Evaluate model performance, accuracy, stability, reliability, and business impact • Partner with engineering and technology teams to deploy and operationalize models within the business • Collaborate with business leaders and stakeholders to define objectives, key metrics, constraints, and success criteria • Identify and prioritize high-impact opportunities where data science can improve business performance • Communicate analytical findings, recommendations, assumptions, and risks to technical and non-technical audiences • Ensure solutions are actionable, interpretable, and aligned with business needs and strategic objectives

🎯 Requirements

• Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics, Operations Research, or a related quantitative field required • Advanced degree in a quantitative field preferred • 7+ years of progressive experience in data science, machine learning, advanced analytics, or a related field • Demonstrated experience developing, deploying, and supporting predictive and machine learning models in production environments • Experience leading complex analytical initiatives from problem definition through adoption • Strong proficiency in Python and/or R for modeling and production-quality code • Strong SQL skills for data exploration and dataset development • Experience with forecasting, optimization, pricing, customer analytics, operational analytics, or related business applications • Familiarity with generative AI, large language models (LLMs), and emerging AI technologies • Experience working in cross-functional environments with engineering, analytics, and business teams • Ability to communicate complex concepts to non-technical stakeholders