Data Science Intern (6 Months) - Architecture optimization for 3D location recommender model
We are Schlumberger, the leading provider of technology and services to the energy industry. Operating in over 120 countries, our people provide leading digital solutions and deploy ground-breaking technologies to unlock cleaner, safer access to energy for every community—including those we live and work in. We’re looking for innovators to join our diverse community of colleagues and develop new solutions and push the limits of what’s possible. If you share our passion for discovery and want to find out what you could really do, then here is the place to do it.
You'll be optimizing the model architecture of a three-dimensional location recommender system. You'll be running experiments against our training and validation datasets and assess the impact on your proposed changes in production using shadow deployment and telemetry.
Essential Responsibilities and Duties:
The core of the project is to find an architecture that exceeds the performance of the current 3D ResNet-based model, including experiments on adding attention mechanisms. Supplementary, depending on the internship duration, you will be 1) revisiting the metrics to optimize against, 2) make performance improvements to the pipelines for feature/label generation and evaluation to enable faster experimentation, 3) work with ML ops team to extend telemetry from production to better assess impact of proposed changes. At the end of the internship you'll have deployed an improved model to production and have been exposed to the full life-cycle of a real-world ML-based project.
Penultimate or final year student, studying towards Bachelors or Masters in Computer Science, Mathematics or related field.
Schlumberger is an equal employment opportunity employer. Qualified applicants are considered without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or other characteristics protected by law.