Lead Data Scientist, Technology

Signature Aviation

Lead Data Scientist at Signature Aviation designing, developing, and deploying data science and machine learning solutions that drive measurable business outcomes.

Posted 5/22/2026full-timeOrlando • Florida • 🇺🇸 United StatesSeniorWebsite

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Design and develop statistical, machine learning, forecasting, and optimization models
Apply techniques such as regression, classification, clustering, time series, and anomaly detection
Translate business problems into scalable analytical approaches and measurable outcomes
Evaluate model performance, accuracy, stability, and business impact
Lead models from concept through production deployment and ongoing optimization
Partner with engineering teams to operationalize models into applications and workflows
Define and support model lifecycle processes, including versioning, monitoring, and retraining
Build reusable, maintainable, and well-documented modeling pipelines
Monitor model performance, drift, and usage; troubleshoot production issues as needed
Collaborate with stakeholders to define objectives, constraints, and success metrics
Identify and prioritize high-value data science opportunities
Communicate results, assumptions, risks, and recommendations clearly to technical and non-technical audiences
Support adoption by ensuring outputs are actionable, interpretable, and aligned to business needs
Perform exploratory data analysis to identify patterns and opportunities
Assess data quality, completeness, and suitability for modeling
Design and validate features that improve model performance
Partner with data teams to enhance analytical datasets and reusable data products
Apply and promote best practices for reproducibility, model governance, and responsible AI
Ensure alignment with enterprise standards for security, privacy, and compliance
Mentor data scientists and analysts on modeling techniques and production readiness
Lead technical and model reviews and contribute to data science standards and frameworks

Requirements

What you’ll need

7+ years of experience in data science, machine learning, statistics, or a related field
Advanced degree in a quantitative field (preferred)
Proven experience developing and deploying 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 working in cross-functional environments (engineering, analytics, business teams)
Ability to communicate complex concepts to non-technical stakeholders

Benefits

Comp & perks

Medical/prescription drug, dental, and vision Insurance
Health Savings Account
Flexible Spending Accounts
Life Insurance
Disability Insurance
401(k)
Critical Illness, Hospital Indemnity and Accident Insurance
Identity Theft and Legal Services
Paid time off
Paid Maternity Leave
Tuition reimbursement
Training and Development
Employee Assistance Program (EAP) & Perks

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

statistical modelingmachine learningforecastingoptimization modelsregressionclassificationclusteringtime seriesanomaly detectionPython

Soft Skills

communicationleadershipcollaborationmentoringproblem-solvinganalytical thinkingstakeholder engagementadaptabilitycritical thinkingproject management