Description

• Partner with stakeholders to identify and execute high-impact AI opportunities that directly drive measurable business outcomes
• Deliver production-grade machine learning models for customer segmentation, churn prediction, and lifetime value estimation to enhance user engagement
• Design and deploy scalable GenAI and LLM solutions that automate complex enterprise workflows, such as transcript analysis and compliance validation
• Build cloud-based data science pipelines on enterprise platforms to ensure the reliability and scalability of analytical products
• Translate complex findings into clear narratives and interactive dashboards that guide executive decision-making
• Foster technical growth across the team by mentoring peers in modern MLOps practices and data storytelling techniques

Skills, Experience and Requirements

 

Core Skills and Competencies (What you’ll bring):

• Critical experiences in applied machine learning, including a track record of delivering high-impact classification, regression, and time-series forecasting solutions
• Advanced AI Application skills, specifically regarding prompt engineering, model evaluation, and the deployment of Large Language Models within production environments
• Technical expertise in Python, Scala, and SQL alongside a deep understanding of modern ML libraries such as TensorFlow, PyTorch, or Scikit-learn
• Hands-on experience with cloud-native data platforms like AWS, Databricks, or Snowflake to manage large-scale data engineering and processing
• Strong collaboration and data storytelling skills that allow for the communication of high-dimensional insights to diverse, non-technical audiences
• Analytical mastery in designing and interpreting A/B tests and controlled experiments to validate model performance and business hypotheses
• Familiarity with MLOps practices for monitoring and maintaining GenAI systems in production

Minimum Requirements:

• Minimum Education: Bachelor’s Degree in Statistics, Machine Learning, Computer Science, Engineering, Mathematics, Physics, or a related quantitative field
• Minimum Experience: 3+ years of experience in data science and applied machine learning
• Required Technical Skills:
  • Python, Scala, and SQL.
  • Machine learning libraries (Scikit-learn, TensorFlow, or PyTorch)
  • Cloud-based AI platforms (AWS, Databricks, or Snowflake)
  • Unstructured data processing for GenAI applications

Key Skills

Education

Bachelor's degree