Job Description
At Supreonix, we are building the future of data-driven innovation. As a Data Analyst, you will transform raw data into actionable insights that drive strategic decisions across our organization. We are looking for a detail-oriented professional who thrives on uncovering trends, optimizing processes, and communicating complex findings to diverse stakeholders. This role offers the opportunity to work with cutting-edge tools and collaborate with cross-functional teams in a fast-paced, supportive environment. You will be part of a culture that values curiosity, continuous learning, and data-backed creativity. Whether you are refining dashboards or exploring new datasets, your work will directly impact product evolution, customer satisfaction, and business growth. Join us to turn data into impact and advance your career in a company that invests in your development.
Requirements
- Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, or a related field
- 2+ years of experience in data analysis or a similar role
- Proficiency in SQL for data extraction and manipulation
- Strong experience with data visualization tools (e.g., Tableau, Power BI, or similar)
- Solid understanding of statistical analysis and hypothesis testing
- Experience with Python or R for data analysis
- Excellent problem-solving and critical-thinking skills
- Strong communication skills to present insights to non-technical stakeholders
- Ability to work independently in a remote environment
- Experience with cloud platforms (e.g., AWS, GCP, Azure) is a plus
- Familiarity with machine learning concepts is a bonus
- Attention to detail and commitment to data accuracy
Responsibilities
- Analyze large datasets to identify trends, patterns, and actionable insights
- Design and maintain dashboards and reports for key business metrics
- Collaborate with product, marketing, and engineering teams to define data requirements
- Conduct ad-hoc analyses to support strategic decision-making
- Ensure data quality and integrity through validation and cleaning processes
- Present findings and recommendations to stakeholders at all levels
- Develop and document data processes and best practices
- Automate recurring reports to improve efficiency
- Monitor and evaluate the impact of data-driven initiatives
- Support the development of data models and forecasting tools
