Apr 2025 – Present · 1 yr 2 mos · Bengaluru, Karnataka, India · Remote

• 1. Data Collection & Cleaning
• Gather data from multiple sources such as databases, APIs, and CSV/Excel files.
• Perform data preprocessing (handling missing values, duplicates, outliers).
• Ensure data quality and integrity for analysis.
• 2. Data Exploration & Analysis
• Use Python, R, or SQL to explore datasets.
• Generate descriptive statistics and summary reports.
• Identify patterns, correlations, and trends in data.
• 3. Data Visualization
• Create interactive dashboards and visualizations using Matplotlib, Seaborn, Tableau, or Power BI.
• Present findings in clear, insightful charts and graphs.
• 4. Machine Learning & Predictive Modeling
• Assist in building, training, and testing machine learning models (e.g., regression, classification, clustering).
• Use libraries such as scikit-learn, TensorFlow, or PyTorch.
• Optimize models using hyperparameter tuning and validation techniques.
• 5. Statistical Analysis
• Apply hypothesis testing, probability, and statistical inference.
• Work with A/B testing for decision-making.
• 6. Documentation & Reporting
• Maintain clear documentation of workflows, code, and findings.
• Prepare reports or presentations for stakeholders.
• 7. Collaboration
• Work closely with senior data scientists, data engineers, and business analysts.
• Participate in team meetings and brainstorming sessions.
• 8. Learning & Development
• Stay updated with latest data science tools, libraries, and techniques.
• Apply theoretical knowledge to real-world problems.