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 role, you will turn complex data into actionable insights, build predictive models, and support data‑driven decision‑making across the. 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 0–1 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.