About
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.
Responsibilities
•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.
Requirements
•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.
Nice to have
•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.
Conditions
•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
