Data Scientist I

Role Overview

Preferred Travel Group is seeking a Data Scientist I to build advanced analytical models and AI/ML-driven insights across the company’s enterprise data platforms. You will partner with Data Engineering, BI Engineering, and business stakeholders to turn data into actionable intelligence, predictive models, and decision-support tools.

Responsibilities

• Data Science & Modeling
  • Develop, validate, and deploy statistical and machine learning models
  • Perform exploratory data analysis (EDA) to find trends, anomalies, and opportunities
  • Build predictive models such as revenue forecasting, member retention, and segmentation
  • Design and evaluate experiments (including A/B testing where applicable)
  • Create feature engineering strategies for large datasets
• Business & Analytical Translation
  • Translate business requirements into analytical models and measurable outputs
  • Define KPIs/metrics and analytical frameworks with stakeholders
  • Provide data-driven recommendations to support strategic initiatives
  • Support financial, marketing, and operations teams with advanced analytics
• AI & Advanced Analytics
  • Support AI initiatives such as recommendation models, automation, and agents
  • Apply techniques including regression, classification, clustering, time series forecasting, and NLP (where applicable)
  • Evaluate model performance and continuously optimize
• Data Integration & Collaboration
  • Work with Data Engineers to ensure data readiness and pipeline integrity
  • Collaborate with BI Engineering to productionize models into reporting layers
  • Partner with QA to validate data accuracy and model outputs
• Data Governance & Quality
  • Ensure data quality, consistency, and auditability of analytical outputs
  • Document methodologies, assumptions, and model logic
  • Support compliance/audit requirements (e.g., SOC 2 alignment where applicable)

Requirements

• Python or R (required)
• SQL (advanced)
• scikit-learn and at least one of: TensorFlow or PyTorch (or equivalent)
• Experience working with data warehouses (e.g., Snowflake, Azure)
• Visualization tools such as Power BI or Tableau

Nice-to-Haves (implied by description)

• Experience with cloud data platforms (text cuts off after “Cloud platfo…”)
• Experience implementing NLP, time series forecasting, and recommendation systems
• Strong model performance evaluation and optimization practices