Senior Data Scientist (m/f/d)

Job Description

The Data Scientist plays a pivotal role in the development and application of advanced analytics and machine learning models to support the development, monitoring, and maintenance of our data products, including Scores, Attributes, and other Data Services. This role is integral to driving innovation and improving the performance of our products, working closely with our Data Engineering, Product & Tech teams ensuring data-driven decision-making.

The primary purpose of this role is to develop, implement, and maintain machine learning models and analytical solutions that enhance our data products. It also includes the monitoring of our Bureau Data Asset and the continuous improvement of our Bureau Data Ingestion Pipeline.

Main Responsibilities

• Develop and implement machine learning models and advanced analytics solutions
• Monitor the performance and quality of our models and data products
• Perform ad hoc analyses to support product development and decision-making
• Collaborate closely with Data Engineering, Product & Tech teams to understand functional requirements and to ensure proper implementation of analytical solutions, new product features and improve processes
• Ensure model accuracy and integrity through rigorous testing and validation processes
• Document methodologies, processes, and findings to maintain transparency and reproducibility
• Extract, manipulate, and analyze data from data lake to support various product development and monitoring activities
• Support our Legal and Compliance Teams in cases of consumer complaints, questions regarding our Scores and regulatory or policy changes
• Stay up to date on industry trends and new developments in machine learning and data science

Qualifications

• Bachelor’s or Master’s degree in data science, Statistics, Computer Science, or a related field
• Strong analytical and problem-solving skills with keen attention to detail
• Deep knowledge of statistical methods and machine learning algorithms, especially logistic regression and boosted trees and its application
• Proficiency in programming languages such as Python or Scala
• Experience with machine learning frameworks such as XGBoost, PyTorch, or scikit-learn
• Experience with data manipulation and extraction from data lakes or large data storages using SQL and Spark
• Proven ability to analyze complex business and risk processes, translating them into actionable data models

Benefits/Perks

• A high degree of autonomy in a dynamic, internationally oriented organization
• A motivated team that values innovation and collaboration
• Great compensation package and attractive employee benefits
• Flexible working hours and remote work options