Data Scientist

Ferrum Capital, Azerbaijan's first independent factoring company, is announcing a vacancy for a Data Scientist

Founded in 2017, Ferrum Capital is a member of the AGA Group and was established to provide factoring and other financial services to both local and international companies. As Azerbaijan's first independent factoring company, we are dedicated to offering innovative financial solutions.

The mission of Ferrum Capital is to become one of the leading companies chosen by candidates who wish to start their first professional experience with us and develop their careers by advancing within the company.

We are looking for a talented, detail-oriented, and motivated Data Scientist to join our Team. If you are passionate about Artificial Intelligence, Data Science, and building data-driven solutions for real-world problems, we'd love to hear from you.

In this role, you will work on end-to-end data and AI projects, from data collection and preparation to building data and AI pipelines, creating analytical dashboards, and delivering valuable business insights.

Responsibilities of the Data Scientist:

• Collect, extract, and integrate data from various sources, including databases, REST APIs, files, and external data sources.
• Validate data quality and identify inconsistencies, errors, and missing values.
• Clean, process, and prepare structured and unstructured data for analysis and modeling.
• Design, develop, and maintain data pipelines.
• Develop and improve AI and LLM-based pipelines, including prompt engineering, agent workflows, and AI automations.
• Design and maintain data orchestration workflows and improve their reliability and monitoring.
• Build and maintain analytical dashboards and reports.
• Document data structures, SQL tables, dashboards, and data-related processes.

Programming and Data Analysis

• Python (required)
• SQL
• Pandas
• NumPy
• Scikit-learn
• Data Visualization

Machine Learning and AI

• Understanding of Machine Learning concepts
• Supervised and Unsupervised Learning
• Regression and Classification problems
• Feature Engineering and Model Evaluation
• Familiarity with common Machine Learning algorithms such as Decision Trees, XGBoost
• Familiarity with Neural Networks and Deep Learning concepts is a plus.

Strong verbal and written English skills are required.

Talented candidates without prior work experience are also encouraged to apply.