Job VC
Power BI / Data Scientist
Technologies
Description
Responsibilities:
Design, develop, and maintain interactive dashboards and reports using Power BI.
Work with business stakeholders to understand reporting needs, define KPIs, and translate business questions into data-driven insights.
Build and optimize data models, datasets, and reporting layers to support scalable analytics.
Analyze structured and semi-structured data to identify trends, patterns, risks, and opportunities.
Develop data-driven solutions, including statistical analysis, forecasting, segmentation, and predictive models where applicable.
Prepare, clean, transform, and validate data from multiple sources.
Collaborate with data engineers, backend developers, product teams, and business users to ensure data quality and consistency.
Automate recurring reporting and analytical workflows where possible.
Leverage AI-assisted tools to accelerate analysis, improve productivity, and streamline repetitive data tasks.
Requirements:
4+ years of experience in data analytics, business intelligence, or data science roles.
Strong hands-on experience with Power BI, including dashboard development, data modeling, and report optimization.
Solid knowledge of SQL and experience working with relational databases.
Experience with data preparation, transformation, and validation.
Strong understanding of DAX and Power Query.
Experience defining and tracking business KPIs and analytical metrics.
Practical experience with Python or R for data analysis, automation, or modeling.
Understanding of statistical analysis, forecasting, or basic machine learning concepts.
Ability to communicate complex analytical findings to both technical and non-technical stakeholders.
Experience working with large datasets and identifying data quality issues.
Practical hands-on experience with AI-assisted tools such as ChatGPT, Claude, Cursor, GitHub Copilot, or equivalent tools for analytics, coding, documentation, and workflow optimization.
Nice to have:
Experience with Azure data services, AWS, or other cloud platforms.
Experience with Microsoft Fabric, Azure Synapse, Databricks, or similar data platforms.
Experience building predictive models or ML-powered analytics solutions.
Knowledge of ETL/ELT processes and data warehouse concepts.
Experience with advanced Power BI performance tuning.
Familiarity with data governance, access management, and row-level security.
Experience working in product analytics, finance analytics, marketing analytics, or operational reporting.
Note:
The role description is intentionally high-level at this stage, as some project details are confidential. We will be happy to share more context during the interview process.
Design, develop, and maintain interactive dashboards and reports using Power BI.
Work with business stakeholders to understand reporting needs, define KPIs, and translate business questions into data-driven insights.
Build and optimize data models, datasets, and reporting layers to support scalable analytics.
Analyze structured and semi-structured data to identify trends, patterns, risks, and opportunities.
Develop data-driven solutions, including statistical analysis, forecasting, segmentation, and predictive models where applicable.
Prepare, clean, transform, and validate data from multiple sources.
Collaborate with data engineers, backend developers, product teams, and business users to ensure data quality and consistency.
Automate recurring reporting and analytical workflows where possible.
Leverage AI-assisted tools to accelerate analysis, improve productivity, and streamline repetitive data tasks.
Requirements:
4+ years of experience in data analytics, business intelligence, or data science roles.
Strong hands-on experience with Power BI, including dashboard development, data modeling, and report optimization.
Solid knowledge of SQL and experience working with relational databases.
Experience with data preparation, transformation, and validation.
Strong understanding of DAX and Power Query.
Experience defining and tracking business KPIs and analytical metrics.
Practical experience with Python or R for data analysis, automation, or modeling.
Understanding of statistical analysis, forecasting, or basic machine learning concepts.
Ability to communicate complex analytical findings to both technical and non-technical stakeholders.
Experience working with large datasets and identifying data quality issues.
Practical hands-on experience with AI-assisted tools such as ChatGPT, Claude, Cursor, GitHub Copilot, or equivalent tools for analytics, coding, documentation, and workflow optimization.
Nice to have:
Experience with Azure data services, AWS, or other cloud platforms.
Experience with Microsoft Fabric, Azure Synapse, Databricks, or similar data platforms.
Experience building predictive models or ML-powered analytics solutions.
Knowledge of ETL/ELT processes and data warehouse concepts.
Experience with advanced Power BI performance tuning.
Familiarity with data governance, access management, and row-level security.
Experience working in product analytics, finance analytics, marketing analytics, or operational reporting.
Note:
The role description is intentionally high-level at this stage, as some project details are confidential. We will be happy to share more context during the interview process.