Internship - Data Scientist - Fraud Prevention in - Clamart, France - Schlumberger

Schlumberger
Schlumberger
Entreprise vérifiée
Clamart, France

il y a 3 semaines

Sophie Dupont

Posté par:

Sophie Dupont

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Description

Internship - Data Science - 3

Fraud prevention in purchase order transactions

About SLB
We are a global technology company, driving energy innovation for a balanced planet.

At SLB we create amazing technology that unlocks access to energy for the benefit of all. That is our purpose. As innovators, that's been our mission for 100 years. We are facing the world's greatest balancing act
- how to simultaneously reduce emissions and meet the world's growing energy demands. We're working on that answer. Every day, a step closer.

Our collective future depends on decarbonizing the fossil fuel industry, while innovating a new energy landscape. It's what drives us. Ensuring progress for people and the planet, on the journey to net zero and beyond. For a balanced planet.


Our Purpose
Together, we create amazing technology that unlocks access to energy for the benefit of all.


Job title
Internship - Fraud prevention in purchase order transactions (6 months)


Location
Clamart, France


Description


Fraud detection is important since it helps businesses and organizations identify and prevent fraudulent activity, which can have serious consequences.

Fraud can cause financial losses for businesses and organizations, damage their reputation, and create legal and regulatory problems. There are different approaches how companies can prevent fraud in purchase order transactions.

One step is to implement its own fraud detection software to identify patterns of fraudulent activity in financial transactions and alert its employees.

Fraud detection algorithms typically analyze large amounts of data to identify patterns that are consistent with fraudulent behavior.

Some common types of fraud detection algorithms include:

  • Anomaly detection algorithms: algorithms identify transactions that are unusual or deviate from the norm.
  • Rulebased algorithms: algorithms use a set of predefined rules to identify fraudulent transactions.
  • Machine learning algorithms: algorithms use statistical techniques to analyze data and identify patterns that are indicative of fraudulent activity.
  • Hybrid algorithms: algorithms combine elements of different types of algorithms to improve the accuracy of fraud detection.
This internship involves working on a project using both supervised and unsupervised approaches to identify patterns in high-order data. It includes clustering/classification, dimensionality reduction, anomaly detection, graph and distributed data processing.


Deliverables
code (python), numerical models, Internship presentation and report.


Target Disciplines and Special Skills

  • Penultimate or final year of MSc in Data Science or similar Engineering degree
  • Oral and written communication skills in English
  • Knowledge in applied mathematics, probability & statistics, manifold learning.
  • Proficiency in Python programming and algorithmic development.
  • Experience in scikitlearn/scipy/numpy/pandas/spark.
  • Good motivation, autonomy, teamwork, and ingenuity
  • Knowledge in geology is a plus
SLB 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.

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