PREVISE in London Salary
2 UNDERWOOD ROW LONDON N1 7LQ UNITED KINGDOM
TIN: 09117429
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Earnings on positions in PREVISE
PREVISE is looking for employees for positions:
data scientist
Requirements
- A minimum of 2 years of experience working in a data science or engineering team
- great software engineering skills including expertise in algorithms and data structures
- strong understanding of machine learning techniques and algorithms, as well as techniques for validation and monitoring of algorithm performance
- strong applied statistical skills. Knowledge of time series modelling and prediction would be helpful but not essential
- experience writing production-level code and deploying code to production, including familiarity with packaging, testing and containerization best practices
- understanding of data integration and ETL processes
- proficiency using Python’s data stack, expertise in data manipulation using SQL and experience with version control systems
- A solid understanding of data processing and engineering principles, including ability to clean, transform and wrangle data using Python
Responsibility
- perform data preprocessing, feature engineering, and exploratory data analysis to uncover hidden patterns and trends
- build and maintain automated systems for extraction, processing, cleansing, and verifying the integrity of the data used for analysis
- evaluate third party sources of data and information, integrating them, and enhancing our data collection procedures
- collaborate with data engineers to build efficient data pipelines, ensuring seamless flow of data for modelling and analysis
- measure and monitor the performance of the implemented systems, including performance reporting
- communicate findings and insights to both technical and non-technical stakeholders through visualisations, presentations, and reports
- build and optimise our machine learning algorithms and our risk and simulation models using modern machine learning techniques to support our origination, our underwriting, and our risk management