Applied Data Scientist

Professional Staffing Services Group • Orlando, FL

1d • Remote

About The Position

Our client drives innovative, data‑driven insights and scalable AI solutions across the entertainment ecosystem. The Data Science team partners with data engineering, marketing, product, and executive teams to transform audience data into actionable strategies and operational products. A successful Applied Data Scientist thrives on both analytical creativity and production rigor. As a key member of our client's team, you will own end‑to‑end modeling and deployment work-from the conceptual framing of business problems to data ingestion, model development, and reliable production delivery. Your work will directly shape how our company delivers value to clients and internal stakeholders.

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 proven ownership of model productization, monitoring, and iterative improvement.
• 3+ years of building machine learning models for business applications (outside of academia) , with deep expertise in both supervised and unsupervised learning algorithms.
• Python: Strong programming skills with hands-on experience building, training, deploying, and monitoring ML models.
• SQL: 2+ years of experience with database querying, data preparation, and analysis.
• Working knowledge of large-scale platforms (e.g., Snowflake, SQL Server, BigQuery, Redshift).
• Familiarity with cloud environments (AWS, Azure, or GCP) and designing end-to-end ML pipelines from ingestion to production serving.
• Outstanding analytical skills to diagnose and resolve complex system issues, with a proven ability to manage multiple projects and prioritize tasks effectively.

Nice To Haves

• 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) or working with data labeling, taxonomy design, and classification frameworks.
• Familiarity with GenAI techniques, language modeling, or frameworks like AWS Bedrock and Hugging Face.
• Advanced experience with tools like SageMaker, Lambda, Airflow, or MLflow, and the ability to guide architectural/strategic decisions for ML infrastructure.

Responsibilities

• Translate ambiguous business questions into structured analytical and ML solutions.
• Develop, validate, and optimize models impacting forecasting, segmentation, personalization, recommendation, or operational efficiency.
• Build production‑ready pipelines and deploy models into scalable environments using robust MLOps practices (CI/CD, automated testing, monitoring), ensuring long-term lifecycle maintenance.
• Partner cross-functionally to bridge business requirements and technical design.
• Communicate insights and technical decisions clearly to both technical and non‑technical stakeholders.
• Document all models, pipelines, and deployment processes comprehensively to ensure maintainability, reproducibility, and knowledge sharing.
• Stay ahead of emerging tools, techniques, and frameworks in ML/AI to influence best practices across the organization.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior