We are seeking a dynamic and detail-oriented Data Analyst to join our team. The ideal candidate will bridge the gap between technical data management and strategic business insights, leveraging data to inform decision-making across both technology operations and business functions. This role will involve analyzing complex datasets, creating insightful reports, and providing actionable recommendations to drive operational efficiency and strategic growth.Key Responsibilities:
●Analyze large datasets to identify trends, patterns, and insights that inform business and technology decisions.
●Develop and maintain dashboards, visualizations, and ad hoc reports for stakeholders in both technology and business units.
●Ensure data quality, accuracy, and consistency across all reports.
●Collaborate with business teams to understand key performance indicators (KPIs) and translate them into actionable reports.
●Provide insights into customer behavior, financial performance, and operational efficiency to support strategic planning.
●Design and implement predictive models to forecast trends and support decision-making.
●Partner with IT teams to ensure seamless integration of data systems and tools.
●Assist in the implementation of data automation and reporting tools to streamline workflows.
●Support the identification and resolution of data discrepancies or technical challenges.
●Act as a liaison between business and technical teams to align data strategies with organizational goals.
●Bachelor’s degree in Data Analytics, Computer Science, Statistics, Business Administration, or a related field. Master’s degree is a plus.
●2+ years of experience as a Data Analyst or similar role, preferably within the finance or technology sector.
●Proven track record of delivering impactful business and technology reports.
●Proficiency in SQL for data querying and manipulation.
●Hands-on experience with data visualization tools such as Tableau, Power BI, or Looker.
●Strong analytical and statistical skills, with experience in tools like Python, R, or Excel.
●Proficiency in data manipulation and analysis libraries such as Pandas and NumPy for efficient data handling and computations.
●Familiarity with cloud data platforms (e.g., AWS,Google Cloud) is a plus.