About the Role
We are looking for a Data Analyst with strong analytical skills and hands-on experience in machine learning to join our growing team. In this role, you will turn complex data into actionable insights, build predictive models, and support data-driven decision-making across the organization. You'll collaborate closely with cross-functional teams to identify business opportunities, design analytical solutions, and drive innovation using data and AI.
Key Responsibilities
Data Analysis & Reporting:
- Collect, clean, and analyze structured and unstructured data from various sources.
- Develop dashboards, reports, and visualizations to present insights and business performance metrics.
- Identify trends, patterns, and correlations that drive strategic decisions.
Machine Learning & Predictive Modeling:
- Build and deploy machine learning models (e.g., regression, classification, clustering, recommendation systems) to solve business problems.
- Evaluate model performance and continuously optimize for accuracy and scalability.
- Collaborate with data engineers to integrate ML models into production environments.
Business Insights:
- Work with stakeholders to define analytical requirements and translate them into actionable data solutions.
- Support experimentation, A/B testing, and forecasting activities.
- Communicate complex findings in a clear and concise manner to non-technical audiences.
Data Governance & Quality:
- Ensure data accuracy, consistency, and security across platforms.
- Develop and maintain documentation for data processes and models.
Qualifications
- Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
- Fresh graduate or 01 year of professional experience as a Data Analyst or related role.
- At least one internship experience in data analytics, data science, business intelligence, or a related field.
- Solid proficiency in Python (pandas, numpy; basic knowledge of scikit-learn is a plus) and SQL.
- Basic understanding of statistical analysis, data modeling, and exploratory data analysis (EDA).
- Exposure to machine learning concepts or projects (academic or internship-based); hands-on experience with TensorFlow or PyTorch is a plus.
- Experience using data visualization tools such as Power BI, Tableau, Looker, or similar tools.
- Familiarity with Git/version control and basic exposure to cloud platforms (AWS, GCP, or Azure) is an advantage.
- Strong analytical thinking, problem-solving skills, and ability to communicate insights clearly through data storytelling.
- Eager to learn, detail-oriented, and able to work well in a fast-paced, collaborative environment.
