Data Scientist Engineer, Digital Experience

What you'll do

• Develop machine-learning models for prediction, time-series forecasting, clustering, churn reduction, anomaly detection, and recommendations.
• Apply statistical and computational methods to large datasets and create executive-level visualizations.
• Partner with Product, Engineering, and Business leaders to turn analytical findings into actionable strategy.

What they ask for

• Master’s degree or Ph.D. in a quantitative discipline such as Computational Methods, Physical Science, Statistics, Applied Mathematics, or Data Science.
• 5 to 8+ years applying machine learning, statistical modeling, and quantitative research.
• Track record in quantitative research and experimental design, with publications or presentations of scientific or computational research, or patents.
• Advanced proficiency in Python and SQL; hands-on experience with the named ML and statistics libraries.

Pay

$217,000 — $326,000 USD (base salary)

Tools

Python, SQL, Scikit-Learn, TensorFlow/Keras, PyTorch, Pandas, Statsmodels

AI focus

Develops predictive and statistical machine-learning models, including time-series prediction, clustering, churn reduction, anomaly detection, and recommendation systems.