B2B rəqəmsal marketinq kampaniyalarını təhlil edir və məlumat analizində 2+ il təcrübəsi tələb olunur.
Vakansiya haqqında
Job Requirements
- Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field.
- 2+ years of professional experience as a Data Scientist or in a similar data-focused role.
- Strong proficiency in Python and experience with data analysis and machine learning libraries.
- Strong SQL skills and hands-on experience with MySQL, PostgreSQL, and ClickHouse.
- Practical experience working with Data Warehouses (DWH) and large-scale datasets.
- Hands-on experience in developing, evaluating, optimizing, and maintaining Machine Learning models.
- Experience with ML model deployment and productionization is highly desirable.
- Experience with Airflow for data and ML pipeline orchestration.
- Experience with Git and collaborative software development practices.
- Experience with Power BI and Tableau, including dashboard development and data visualization.
- Understanding of ETL/ELT processes, data pipelines, and data engineering concepts.
- Strong analytical, problem-solving, and communication skills.
- Experience in online payments, financial services, banking, or FinTech is an advantage.
Job Responsibilities
- Develop, evaluate, optimize, and maintain Machine Learning models for business and product-related use cases.
- Perform data analysis and exploratory data analysis to identify trends, patterns, business opportunities, and potential risks.
- Work with large datasets and complex data sources to prepare, transform, and analyze data for analytical and ML use cases.
- Design and implement data preparation and feature engineering pipelines for Machine Learning models.
- Work closely with the Data Warehouse (DWH) and analytical data infrastructure, including ClickHouse, PostgreSQL, and MySQL.
- Develop and maintain Airflow pipelines for data processing, model scoring, and ML workflows.
- Contribute to ML model deployment and automation of model scoring and related workflows.
- Monitor model performance and contribute to model optimization, retraining, and lifecycle management.
- Use Git for version control and collaborate with other team members on data and ML projects.
- Prepare and maintain technical documentation for Machine Learning models, data pipelines, methodologies, and analytical processes.
- Build analytical dashboards in Power BI and Tableau when required, enabling clear visualization of data, insights, trends, and business KPIs.
- Translate business requirements into data-driven solutions and analytical models.
- Collaborate with Data Analysts, Data Engineers, Product, Business, and other stakeholders to deliver data-driven solutions.
- Continuously improve existing analytical processes, ML models, pipelines, and reporting solutions.
Work schedule: 5 days a week, 09:00-18:00
To apply, please send your CV to the e-mail address in the Apply for job button with the name of the vacancy.
Applications will be evaluated based on the requirements of the vacancy and selected candidates will be contacted.
Job Requirements
- Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field.
- 2+ years of professional experience as a Data Scientist or in a similar data-focused role.
- Strong proficiency in Python and experience with data analysis and machine learning libraries.
- Strong SQL skills and hands-on experience with MySQL, PostgreSQL, and ClickHouse.
- Practical experience working with Data Warehouses (DWH) and large-scale datasets.
- Hands-on experience in developing, evaluating, optimizing, and maintaining Machine Learning models.
- Experience with ML model deployment and productionization is highly desirable.
- Experience with Airflow for data and ML pipeline orchestration.
- Experience with Git and collaborative software development practices.
- Experience with Power BI and Tableau, including dashboard development and data visualization.
- Understanding of ETL/ELT processes, data pipelines, and data engineering concepts.
- Strong analytical, problem-solving, and communication skills.
- Experience in online payments, financial services, banking, or FinTech is an advantage.
Job Responsibilities
- Develop, evaluate, optimize, and maintain Machine Learning models for business and product-related use cases.
- Perform data analysis and exploratory data analysis to identify trends, patterns, business opportunities, and potential risks.
- Work with large datasets and complex data sources to prepare, transform, and analyze data for analytical and ML use cases.
- Design and implement data preparation and feature engineering pipelines for Machine Learning models.
- Work closely with the Data Warehouse (DWH) and analytical data infrastructure, including ClickHouse, PostgreSQL, and MySQL.
- Develop and maintain Airflow pipelines for data processing, model scoring, and ML workflows.
- Contribute to ML model deployment and automation of model scoring and related workflows.
- Monitor model performance and contribute to model optimization, retraining, and lifecycle management.
- Use Git for version control and collaborate with other team members on data and ML projects.
- Prepare and maintain technical documentation for Machine Learning models, data pipelines, methodologies, and analytical processes.
- Build analytical dashboards in Power BI and Tableau when required, enabling clear visualization of data, insights, trends, and business KPIs.
- Translate business requirements into data-driven solutions and analytical models.
- Collaborate with Data Analysts, Data Engineers, Product, Business, and other stakeholders to deliver data-driven solutions.
- Continuously improve existing analytical processes, ML models, pipelines, and reporting solutions.
Work schedule: 5 days a week, 09:00-18:00
To apply, please send your CV to the e-mail address in the Apply for job button with the name of the vacancy.
Applications will be evaluated based on the requirements of the vacancy and selected candidates will be contacted.
Şirkət haqqında
Azərbaycanın onlayn ödəmələr bazarında ən böyük şirkət GoldenPay ASC 2007-ci ilin iyul ayında yaranmışdır. Şirkət 2 il ərzində sistemdə aparılan texniki işlərin yekunlaşması və “Visa”/ “MasterCard” kimi beynəlxalq ödəniş sistemlərindən…
Golden Pay — bütün vakansiyalarBacarıqlar və texnologiyalar
Müraciətin
Bacarıqlara görə oxşar
Bütün oxşar vakansiyalarBu vakansiyanın bacarıqları ilə ən çox üst-üstə düşən vakansiyalar.
Reklam kampaniyalarının performansını təhlil edir və optimallaşdırır, 2+ il data analiz təcrübəsi tələb olunur.
Məlumatların toplanması, emalı və AI həllərinin hazırlanması üçün Python və Data Engineering bacarıqları tələb olunur
Məlumatları təhlil edərək qiymət optimallaşdırma strategiyaları hazırlamaq üçün analitik bacarıq tələb olunur.


