Applied Data Scientist

What you’ll get: a contract-to-hire Applied Data Scientist opportunity with a Florida-based team and hybrid flexibility. This role supports end-to-end work from modeling through production deployment, with a focus on robust MLOps practices. Compensation is approximately USD 140,000 to 185,000 per year. Sponsorship is not available now or in the future.

Where you’ll work: Orlando, FL (hybrid). Day One requires travel to Orlando, FL (or the closest office local to your area) for onboarding. After that, you’ll travel occasionally to Orlando (or your closest local office) for meetings, trainings, and business support. Candidates must reside in Florida or live in GA, TX, and NC and be able to meet the travel expectations.

Responsibilities

• Convert ambiguous business questions into structured analytical and machine learning solutions, building, validating, and optimizing models for use cases such as forecasting, segmentation, personalization, recommendation, or operational efficiency.
• Create production-ready pipelines and deploy models into scalable environments using strong MLOps practices, including CI/CD, automated testing, and monitoring, with a focus on long-term lifecycle maintenance.
• Collaborate cross-functionally to align business needs with technical design, and communicate model insights and technical decisions clearly to both technical and non-technical stakeholders.
• Document models, pipelines, and deployment processes thoroughly to support maintainability, reproducibility, and knowledge sharing.
• Stay current on emerging ML/AI tools, techniques, and frameworks to help shape and improve organizational best practices.

Requirements

• Bachelor’s degree in Computer Science, Statistics, Mathematics, or a related quantitative field.
• 5+ years of industry experience (excluding internships) in data science and machine learning, including demonstrated ownership of model productization, monitoring, and iterative improvement.
• 3+ years building machine learning models for business applications (outside of academia), with deep expertise in both supervised and unsupervised learning.
• Strong hands-on programming skills in Python, including building, training, deploying, and monitoring ML models.
• 2+ years of experience with SQL for database querying, data preparation, and analysis.
• Working knowledge of large-scale platforms such as Snowflake, SQL Server, BigQuery, or Redshift.
• Familiarity with cloud environments (AWS, Azure, or GCP) and experience designing end-to-end ML pipelines from ingestion to production serving.
• Excellent analytical skills to diagnose and resolve complex system issues, with the ability to manage multiple projects and prioritize effectively.

Preferred Qualifications

• Master’s or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative field.
• Industry experience in entertainment or e-commerce, including domains such as theme parks, hospitality, live performances, ticketing, or retail marketplaces.
• Hands-on experience designing and deploying recommendation models (collaborative filtering, content-based, transformer-based) and/or work with data labeling, taxonomy design, and classification frameworks.
• Familiarity with GenAI techniques such as language modeling, including frameworks like AWS Bedrock and Hugging Face.
• Advanced experience with tools such as SageMaker, Lambda, Airflow, or MLflow, with the ability to guide architectural and strategic decisions for ML infrastructure.

Technologies

Python, SQL, Snowflake, SQL Server, BigQuery, Redshift, AWS, Azure, GCP, CI/CD, automated testing, monitoring

Travel & Work Location Notes

• Ability to commute is preferred to Orlando, FL 32819.
• Willingness to travel is listed as 25% (preferred).

Application Prompt

Please specify whether you have experience within the entertainment or ecommerce industry.