Position: Data Analyst / Data Science
Company: PLATMA
Experience required: 2y
English level: intermediate

We are looking for a Data Analyst / Data Scientist candidate who has experience with databases, has a high level of knowledge and experience with Python programming, and understands the principles of building machine learning models. Our ideal candidate should be able to detect anomalies in data and have experience in building scoring systems to assess risks and benefits to the business. You will analyze large volumes of data to identify valuable insights and support decision making, and ensure clear communication of your work to the customer and colleagues.

Requirements:

Database knowledge:
● Experience with Postgre databases and the ability to effectively optimize database queries to work with large amounts of data (from 1 TB).
● Knowledge of SQL to collect, process and analyze data.

Programming language:
● High level of knowledge and experience with Python, the main programming language for analytical tasks.
● Ability to work with Python libraries for data analysis and machine learning, such as Pandas, NumPy, Scikit-learn, etc.

Machine Learning:
● Deep understanding of the principles of building machine learning models.
● Experience with various machine learning methods and the ability to choose the most appropriate algorithms for specific tasks.
● Experience with machine learning on big data will be an advantage.

Search for anomalies:
● Knowledge of methods and practical experience in detecting anomalies in data.
● Ability to identify anomalous behaviors that may indicate problems or potential threats.

Experience in building scoring systems:
● Experience developing scoring systems to assess risks or potential business benefits.
● Ability to work with financial transactions or other business areas to build effective scoring systems.

Benefits:
● Opportunities for professional growth and development.
● Access to cutting-edge technologies and tools.
● A dynamic, fast-paced work environment.
● Flexible work arrangements.
● The opportunity to work on projects that have a meaningful impact on society.