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Weekday (YC W21)Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in data science and machine learning, with strong programming skills in Python and experience in developing reproducible environments and evaluation frameworks. Capable of identifying methodological weaknesses and ensuring solution quality through rigorous testing and validation.
Highest-signal resume keywords
Data ScienceMachine LearningPython ProgrammingStatistical AnalysisAutomated Testing
Tech Stack
Tools & technologiesAbout the role
Key responsibilities & impact- Design challenging data science, machine learning, and mathematical modeling tasks based on real-world problems and competitive programming experience
- Build reproducible execution environments, prepare datasets, configure dependencies, and ensure consistent task execution
- Implement accurate, efficient, and verifiable reference solutions
- Develop automated tests, validation criteria, and evaluation frameworks to distinguish correct solutions from incomplete, inefficient, or flawed implementations
- Run AI coding agents against designed tasks, analyze performance, investigate failure patterns, and refine task specifications
- Identify implementation bugs, incorrect assumptions, data leakage, methodological weaknesses, and other issues affecting solution quality
- Document problem statements, expected outputs, solution methodologies, dependencies, and verification procedures
- Improve task complexity, reproducibility, and evaluation reliability through iterative testing and experimentation
Requirements
What you’ll need- Demonstrated experience in data science, machine learning, quantitative modeling, applied mathematics, or a related technical field
- Participation in competitive data science or machine learning platforms, such as Kaggle, DrivenData, Zindi, AIcrowd, Numerai, DataSource.ai, or CodaLab/Codabench
- Strong analytical reasoning and ability to break down complex problems into structured, testable solutions
- Practical programming skills sufficient to independently implement, test, debug, and validate technical solutions
- Understanding of statistical methods, predictive modeling, data preprocessing, feature engineering, and model evaluation
- Ability to identify data leakage, overfitting, flawed assumptions, and methodological errors
- Experience evaluating model performance and validating results against reliable benchmarks
- Strong attention to detail and ability to communicate technical reasoning clearly
- Competitive data science
- Kaggle competitions
- Machine learning
- Python programming
- Statistical analysis and mathematical reasoning
- Data modeling and model evaluation
- Testing, debugging, and solution validation
- Experience with DrivenData, Zindi, AIcrowd, Numerai, or similar competition platforms
- Strong Python development skills, including working with unfamiliar codebases
- Experience with pandas, NumPy, scikit-learn, PyTorch, or TensorFlow
- Knowledge of automated testing, reproducible environments, and dependency management
- Experience developing evaluation benchmarks and automated grading systems
- Familiarity with AI coding agents, LLM-based development tools, and agent evaluation
- Experience in quantitative research, optimization, feature engineering, and advanced statistical modeling
Benefits
Comp & perks- Fully remote work arrangement
- Flexible schedule — choose preferred working hours and days, including weekends
- Contractor schedule of approximately 15 hours per week
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Quantitative ModelingApplied MathematicsData PreprocessingFeature EngineeringModel EvaluationTestingDebuggingSolution ValidationStatistical MethodsPerformance Evaluation
Soft Skills
Analytical ReasoningAttention to DetailClear Communication
Tools & Technologies
PandasNumPyScikit-LearnPyTorchTensorFlowKaggleDrivenDataZindiAIcrowdNumerai
Industry Keywords
Competitive Data ScienceMathematical ModelingReproducible EnvironmentsEvaluation FrameworksAI Coding Agents