Data Scientist developing and implementing LLM - based agents and leveraging AI techniques to improve client value. Collaborating on project challenges in a dynamic, start - up environment at Gartner.
About the role
- Data Science Intern developing machine learning solutions for fraud detection at GeoComply. Collaborating with data scientists to solve real-world challenges and gain hands-on experience in a fast-paced environment.
Responsibilities
- Support ML Model Development: Assist in building, testing, and validating machine learning models for fraud detection and anomaly detection under guidance from senior data scientists.
- Conduct Data Analysis & Exploration: Perform exploratory data analysis to identify patterns, trends, and insights in large-scale transaction datasets.
- Feature Engineering & Data Preparation: Help develop features, clean and preprocess data, and prepare datasets for model training and evaluation.
- Model Evaluation & Testing: Run experiments, evaluate model performance using standard metrics, and document findings clearly.
- Research & Learning: Investigate new fraud patterns, research ML techniques, and stay current with industry best practices in fraud detection and data science.
- Collaborate & Learn: Work closely with data analysts, data scientists, and engineers; participate in code reviews and team meetings to develop professional skills.
- Documentation: Maintain clear documentation of analysis methods, code, and results to support knowledge sharing.
Requirements
- Currently pursuing or recently completed a Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Data Science, Machine Learning, or related quantitative field.
- Strong academic record with relevant coursework in machine learning, statistics, or data analysis.
- Solid programming skills in Python with familiarity with data manipulation libraries (Pandas, NumPy).
- Basic understanding of machine learning concepts and algorithms (classification, regression, clustering).
- Working knowledge of SQL for data extraction and basic queries.
- Familiarity with data visualization tools (Matplotlib, Seaborn, or similar).
- Basic understanding of statistical concepts and experimental methods.
- Experience with Jupyter notebooks or similar development environments.
- Familiarity with version control (Git) is a plus.
- Strong curiosity and eagerness to learn new technologies and techniques.
- Good problem-solving skills with attention to detail.
- Ability to work independently and ask thoughtful questions when guidance is needed.
- Good communication skills with ability to explain technical concepts clearly.
- Self-motivated with ability to manage time and priorities effectively.
Benefits
- Competitive internship compensation
- Premium health insurance coverage
- In-office snacks and drinks (snacks, coffee, juice, milk, etc.)
- International working environment
- Opportunity to work on high-impact projects
- Hybrid working mode & Modern office at a prime location in District 1
Job title
Job type
Experience level
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