Amisha Sinha
Melbourne,VIC
Summary
Data Scientist with strong analytical and problem-solving skills. Adept at leveraging data to drive actionable insights and support business goals. Skilled in Python, R, and SQL, with focus on machine learning and statistical analysis. Reliable team player, adaptable to changing needs, and consistently delivers results through collaboration and effective communication.
Overview
6
6
years of professional experience
Work History
Retail Assistant
Aldi
12.2022 - Current
- Assisted customers with inquiries, enhancing overall shopping experience.
- Managed inventory levels, ensuring product availability and organization.
- Operated cash register accurately, processing transactions efficiently.
- Collaborated with team members to maintain store cleanliness and visual standards.
- Trained new staff on operational procedures and customer service best practices.
- Implemented merchandising strategies to maximize product visibility and sales.
- Analyzed sales data to identify trends and inform restocking decisions.
- Stocked merchandise, clearly labeling items, and arranging according to size or color.
- Replenished sales floor merchandise and organized shelves, racks, and bins for optimal appearance.
- Greeted customers, helped locate merchandise, and suggested suitable options.
- Maintained tidy and organized store environment to comply with cleanliness standards.
- Processed transactions accurately, balancing cash registers at the end of each shift.
Frontend Developer
MusicalMoon
07.2025 - 11.2025
- Developed responsive web applications using HTML, CSS, and JavaScript frameworks.
- Used Docker and Xcode for web and mobile app development.
- Collaborated with designers to create user-friendly interfaces and enhance user experience.
- Implemented version control systems like Git for efficient code management and collaboration.
- Conducted cross-browser testing to ensure consistent performance across multiple platforms.
- Assisted in debugging code and troubleshooting issues to maintain application functionality.
- Participated in team meetings to discuss project progress and contribute ideas for improvements.
- Integrated APIs to enhance application features and streamline data flow between services.
- Maintained documentation of development processes and coding standards for future reference.
- Produced websites compatible with multiple browsers.
Crop Yield Prediction Model
Data Science Professional Project
03.2024 - 07.2024
- Framed crop yield forecasting as a supervised time-series regression problem, using historical weather, soil, and yield data.
- Designed the end-to-end data pipeline: identified data sources (sensors, expert data, surveys), planned cleaning for missing or outlier values, and defined train/test splits for evaluation.
- Sketched an RNN model using LSTM/GRU layers, with dropout, and a linear output layer to predict continuous crop yields from multivariate time-series inputs.
- Consider the trade-offs in network depth, hidden units, and memory limits to balance model complexity, overfitting risk, and training stability.
- Defined an evaluation approach using metrics such as MAE, RMSE, and R², and outlined how model performance would be monitored over time.
- Designed a simple Flask-backed web app concept where farmers enter regional soil and weather details, and receive yield predictions as HTTP responses.
- Planned use of JavaScript and AJAX for sending input data asynchronously to the Flask API, and updating predictions on the page without reloads.
DataAlchemy - Modern Solution to Preventing Fires
Work Integrated Learning (WIL) Project
07.2023 - 11.2023
- I used the “100 Years of Bushfire” UNSW open dataset for NSW and helped research, acquire, and understand geospatial fire history data for modeling and dashboards.
- Performed exploratory data analysis (EDA) on space consumption variables (AreaHa, PerimeterM, Shape_Area, Shape_Length) using time-series plots, pair plots, correlation heatmaps, and boxplots to identify trends, correlations, and outliers.
- Analysed class imbalance and data bias in the fire-type labels (e.g. 2002–03 Wildfire and contributed to the decision to drop non-informative IDs (FID) and apply SMOTE oversampling for fairer model training.
- Worked with the team on a regression modeling pipeline in Python, comparing Linear Regression, Random Forest Regression, and considering SVM regression to predict annual fire sizes and counts from historical and geographic variables.
- Helped define and interpret model evaluation using metrics and visual diagnostics (e.g., comparing linear vs. non-linear fits, and seasonal patterns, to understand how well models captured temporal and spatial fire behavior.
- Designed and built the Historical Analysis dashboard (Monday.com) with configurable filters (year, region, season, fire type), and visualizations (time series, pie charts, summary tables) so users can explore NSW fire history without touching raw data.
- Collaborated on integrating model outputs into a predictive analysis dashboard with geospatial maps showing predicted fire intensity and location over time, supporting resource planning and risk communication.
Receptionist
Kumon Learning Center
11.2019 - 06.2021
- Managed front desk operations, ensuring efficient customer service and communication with parents and students.
- Handled inquiries and provided information about programs, fostering a welcoming environment for families.
- Maintained accurate student records and enrollment data using proprietary software systems to ensure compliance.
- Marked student assessments, and updated data on student profiles.
- Resolved customer problems and complaints.
- Streamlined front desk operations for increased efficiency by effectively managing phone calls, emails, and walk-in clients.
- Responded to inquiries from callers seeking information.
- Corresponded with clients through email or telephone.
- Handled sensitive information with discretion while maintaining strict confidentiality standards.
Education
Bachelor of Data Science - Data Science
RMIT University
Melbourne12-2025
Skills
- Python Programming
- R Programming
- SQL Programming
- JavaScript (Frontend: CSS and Typescript)
- Hadoop/Apache Spark (Big Data Processing and Analysis)
- Machine learning
Timeline
Frontend Developer
MusicalMoon
07.2025 - 11.2025
Crop Yield Prediction Model
Data Science Professional Project
03.2024 - 07.2024
DataAlchemy - Modern Solution to Preventing Fires
Work Integrated Learning (WIL) Project
07.2023 - 11.2023
Retail Assistant
Aldi
12.2022 - Current
Receptionist
Kumon Learning Center
11.2019 - 06.2021
Bachelor of Data Science - Data Science
RMIT University