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Signature Aviation

Lead Data Scientist, Technology

Career Insights for Generative Artificial Intelligence Engineer

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What they do

A Generative Artificial Intelligence Engineer develops, designs, and manages generative models and algorithms that support the generation of new content in the form of images, text, audio, and other multimedia. They utilize GPTs, GANs, VAEs, and other deep learning architectures to craft systems capable of generating data. May work with data scientists, machine learning engineers, and software developers.

$116,959 / year median in Florida

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Job Description

Lead Data Scientist, Technology

Signature Aviation

Orlando, Florida

PERMANENT

Updated 09/03/2026

Job Description

Job Summary

The Lead Data Scientist is responsible for designing, developing, and deploying production-ready data science and machine learning solutions that drive measurable business outcomes. This role operates as a senior individual contributor and technical lead, partnering closely with business, data, engineering, and platform teams to translate complex problems into scalable analytical solutions.

The position owns the full lifecycle of modeling initiatives, from problem definition and model development through deployment, monitoring, and continuous improvement. This role also helps establish standards, best practices, and repeatable patterns to mature enterprise data science capabilities.

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

Additional knowledge and skills:

Experience with machine learning and statistical libraries (e.g., scikit-learn, XGBoost, PyTorch, TensorFlow)

Familiarity with modern data platforms (e.g., Databricks, Snowflake, BigQuery)

Experience with cloud environments (AWS, Azure, or GCP)

Understanding of MLOps practices (model versioning, CI/CD, monitoring, lifecycle management)

Experience building reusable modeling pipelines or scalable data science solutions

Familiarity with tools such as MLflow, Git, and workflow orchestration platforms

Exposure to model governance and responsible AI practices

Experience with forecasting, optimization, pricing, or operational analytics is a plus

Exposure to generative AI or LLM-based solutions is a plus

Experience working in enterprise or matrixed environments is a plus

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

With more than 225 locations worldwide, Signature Aviation is the largest global network of private aviation terminals, delivering safe, convenient, and elevated experiences to those we serve. As a premier hospitality organization and a certified Great Place to Work™, we are committed to redefining private air travel. Our nearly 6,000-strong team of aviation experts and enthusiasts is dedicated to delivering excellence to our guests and communities, and it starts with taking care of our team. Signature provides a variety of benefits, programs, and resources to support our team members' overall well-being and professional development. We proudly volunteer and give back, focusing on elevating the neighborhoods where we operate, empowering the next generation of aviation professionals, and supporting our veterans.

From your health to your financial wellness, there are several benefits for you and your family when joining Signature Aviation.

Our Benefits:

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

Qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity, national origin, or other protected characteristics.

Job and company information not to be copied, shared, scraped, or otherwise disseminated without explicit consent of JSfirm, LLC.

Benefits

  • Paid Time Off (PTO)
  • Financial Aid/Assistance
  • Professional Development
  • 401(k) Plans