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.

Interested candidates can apply by clicking the link

provided in the "Apply" button.