Data Scientist Ii, Amzl, Central Learning Solutions Science

Amazon Amazon · Big Tech · Bellevue, WA · Data Science

This role focuses on developing and implementing machine learning models and statistical methods to personalize learning experiences and assess training effectiveness within Amazon Operations. The Data Scientist will drive the data science roadmap, estimate causal impacts of training, recommend interventions, and measure post-launch success using A/B testing. The role involves establishing scalable processes for data analysis, model development, and validation, and applying advanced causal inference and statistical techniques to solve business problems and improve training outcomes.

What you'd actually do

  1. Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and implementation.
  2. Use advanced causal inference methodologies to estimate the learning curves for different learner profiles and the effectiveness of training content.
  3. Perform statistical analysis and statistical tests including hypothesis testing and A/B testing.
  4. Implement new statistical, machine learning, or other mathematical methodologies to solve specific business problems.
  5. Present deep dives and analysis to both technical and non-technical stakeholders, ensure clarity, and influence the strategy of business partners.

Skills

Required

  • Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science
  • 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
  • 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
  • Experience applying theoretical models in an applied environment
  • 2+ years of data scientist experience

Nice to have

  • Knowledge of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc.
  • Experience with data scripting languages (e.g. SQL, Python, R etc.) or statistical/mathematical software (e.g. R, SAS, or Matlab)
  • Experience with AWS services including S3, Redshift, Sagemaker, EMR, Kinesis, Lambda, and EC2
  • Experience with statistical methods (e.g., A/B Testing, Regression)

What the JD emphasized

  • advanced causal inference methodologies
  • estimate the causal impact of training interventions
  • measure the post-launch success of these interventions through A/B weblabs
  • Implement new statistical, machine learning, or other mathematical methodologies to solve specific business problems.

Other signals

  • develops technology and mechanisms for building personalized learning experiences
  • assess the post-training performance curves
  • leverage your knowledge in statistics and econometrics
  • estimate the causal impact of training interventions
  • recommend the right interventions for a given learner profile
  • measure the post-launch success of these interventions through A/B weblabs
  • dynamically changing the training content of Learning & Development courses
  • improve both training effectiveness and learner experience
  • Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and implementation.
  • Use advanced causal inference methodologies to estimate the learning curves for different learner profiles and the effectiveness of training content.
  • Perform statistical analysis and statistical tests including hypothesis testing and A/B testing.
  • Implement new statistical, machine learning, or other mathematical methodologies to solve specific business problems.