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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Proficient in designing and fine-tuning machine learning models using Python and modern ML frameworks, with a strong foundation in statistics and linear algebra. Experienced in data preprocessing, performance evaluation, and collaborative deployment in production environments.
Highest-signal resume keywords
Python ProgrammingMachine Learning AlgorithmsData PreprocessingSQL ProficiencyCloud Platforms (AWS, GCP, Azure)
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningStatisticsLinear AlgebraData AnalysisModel EvaluationPandasNumPyScikit-LearnPyTorchTensorFlow
Soft Skills
CuriosityPersistenceDebugging
Tools & Technologies
AWSGCPAzureSageMakerVertex AIGit
Industry Keywords
FintechSentiment AnalysisPersonal Expense ClassifierLLMGenAI
Tech Stack
Tools & technologiesAWSAzureCloudGoogle Cloud PlatformNumpyPandasPythonPyTorchScikit-LearnSQLTensorflow
About the role
Key responsibilities & impact- Model Development: Assist in designing, training, and fine-tuning machine learning models using Python and modern ML frameworks.
- Data Pipeline Maintenance: Help clean, preprocess, and analyze large datasets to ensure high-quality training inputs for our models.
- Performance Evaluation: Conduct experiments to evaluate model accuracy, precision, and recall; document findings and iterate based on performance metrics.
- Research & Implementation: Stay up-to-date with the latest developments in AI/ML and explore how they can be applied to solve specific fintech problems.
- Collaborative Deployment: Work with the engineering team to integrate model prototypes into our production environment.
Requirements
What you’ll need- Education: Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related quantitative field.
- Technical Toolkit: Proficiency in Python (specifically libraries like Pandas, NumPy, Scikit-Learn, PyTorch, or TensorFlow). Back-end or full-stack knowledge.
- Statistical Foundation: A solid understanding of machine learning algorithms, statistics, and linear algebra.
- Data Fluent: Comfortable working with SQL to query and manipulate large datasets.
- Curious & Persistent: You love debugging complex issues and are comfortable with the iterative nature of ML model building.
- Nice to have
- Experience with cloud platforms (AWS, GCP, or Azure) and machine learning services (e.g., SageMaker, Vertex AI).
- Exposure to LLM and GenAI.
- Previous experience or passion projects in the fintech space (e.g., building a sentiment analysis tool for markets, or a personal expense classifier).
- Familiarity with version control systems like Git.
Benefits
Comp & perks- Inspiring Office Environment: When you come to the mylo office, you'll find creative workspaces, an open design that encourages team collaboration, and a well-equipped kitchen for your daily coffee breaks or snack moments.
- Learn from the Best: You’ll be surrounded by experienced, passionate tech professionals who are ready to guide you. You'll learn fast, grow even faster, and gain real-world exposure that will help you take confident steps in your career.
- Real Impact: This isn’t a “watch-and-learn” kind of internship. You’ll be working on real projects, solving actual problems, and making a difference — from day one.
