BI data scientist

HFM is an internationally acclaimed multi-asset broker, delivering cutting-edge trading tools, platforms, and conditions to traders worldwide. We are committed to innovation, transparency, and excellence in the financial markets. As we continue to expand, we are seeking a driven and strategic BI Data Scientist to join our team.

• Design and maintain analytical data models to support advanced analytics, reporting, and machine learning workflows.
• Utilize SQL and Python to clean, process, transform, and analyze datasets efficiently.
• Perform exploratory data analysis to identify trends, patterns, relationships, anomalies, and areas for further investigation.
• Support the development and implementation of predictive and machine learning models for use cases such as forecasting, customer segmentation, behavior prediction, and other business applications.
• Perform data preprocessing and feature engineering to prepare high-quality datasets for machine learning and predictive modeling.
• Assist with the evaluation and validation of machine learning and predictive models using appropriate statistical and performance metrics.
• Support the integration of data science models into BI and operational workflows in collaboration with data engineering and other technical teams.
• Monitor model performance and contribute to the continuous improvement of predictive and analytical solutions.
• Develop DAX measures for business calculations, KPIs, and analytical requirements in Power BI.
• Create interactive dashboards and visualizations in Power BI to communicate analytical findings, model outputs, KPIs, and business insights effectively.
• Support the development and maintenance of ETL/ELT processes required for analytics and machine learning workflows.
• Conduct unit testing and validation to ensure accuracy, consistency, and reliability across analytical solutions.
• Follow data governance, security, privacy, and data quality standards across analytical and machine learning solutions.
• Collaborate with data engineering teams to improve data availability, storage, and processing solutions required for advanced analytics.
• Work with analysts and business stakeholders to understand business requirements and translate analytical findings into actionable insights.
• Create and maintain technical documentation for data models, analytical methodologies, machine learning models, queries, and related processes.
• Support knowledge sharing across BI teams and provide guidance to business users on analytical tools, dashboards, and data-driven decision-making.

• University degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.
• Minimum of 1–2 years of experience in data analytics, data science, BI, or related data-driven roles.
• Previous experience in the FX industry is considered an advantage.
• Experience or exposure to data science projects involving customer analysis, behavior prediction, segmentation, forecasting, or similar predictive analytics applications.
• Good SQL scripting skills, including the ability to develop and optimize queries for analytical purposes.
• Good proficiency in Python for data analysis, machine learning, statistical modeling, and workflow automation.
• Good understanding of machine learning techniques and algorithms, including supervised and unsupervised learning approaches.
• Experience with data preprocessing, feature engineering, model evaluation, and validation.
• Understanding of data modeling concepts, analytical models, and data warehouse structures.
• Experience with Power BI for developing reports, dashboards, and data visualizations.
• Working knowledge of DAX for business calculations, measures, and KPIs in Power BI.
• Familiarity with version control systems for managing analytical code, scripts, models, and related development work.
• Ability to understand business requirements and translate them into analytical and data science solutions.
• Strong analytical, problem-solving, and critical-thinking abilities.
• Good communication and collaboration skills, with the ability to present analytical findings to technical and non-technical stakeholders.
• Excellent command of the English language.
• Resumes must be submitted in English.
• Applicants must be eligible or have legal authorization to work in the country where the position is based.
• Будет плюсом: Hands-on experience developing or supporting ETL/ELT pipelines for data integration and transformation; Exposure to machine learning model deployment, monitoring, or integration into production or BI environments; Familiarity with statistical modeling, experimentation, or hypothesis testing; Knowledge of SQL Server Analysis Services (SSAS) for OLAP modeling; Exposure to Microsoft Fabric Cloud Services or Azure Data Services for cloud-based analytics and machine learning solutions; Experience working with large-scale or real-time datasets; Basic understanding of MLOps concepts, model lifecycle management, or CI/CD practices for data science solutions

• Hybrid Work Model (2 days working from home)
• Wolt Meal Allowance
• Comprehensive Health Insurance
• Provident Fund (Upon completion of the trial period)
• Summer Short Fridays (August)
• Additional Paid Annual Leave (up to 30 days, based on years of service)
• Birthday Leave
• Udemy Business access
• Gym Membership
• Referral Bonus Program
• Additional Support Visa Sponsorship and Relocation Assistance