Data Analyst @ Crossing Hurdles
placeHybrid
attach_money $78,000
businessHybrid
scheduleContractor
Posted 22 days ago
Your Application Journey
Interview
Email Hiring Manager
******* @crossinghurdles.com
Recommended after applying
Job Details
Overview
Crossing Hurdles is a recruitment firm referring top candidates to world-leading AI research labs. As a Data Analyst, you will help build and train cutting-edge AI models by analyzing large, structured datasets.
Role Responsibilities
- Analyze large structured datasets provided by partner organizations.
- Design reasoning-based analytics questions requiring multi-step problem-solving.
- Write and validate Snowflake SQL queries using DuckDB, pandas, or Python notebooks.
- Produce clear, human-readable explanations of analytical insights.
- Format deliverables into structured JSON outputs including question, query, and answer components.
- Collaborate with peers to ensure consistency and quality.
Ideal Qualifications
- Strong experience in data analytics, data science, or a related quantitative field.
- Proficiency in SQL and Python, with experience in DuckDB and pandas.
- Expertise in data exploration, statistical reasoning, and business intelligence.
- Familiarity with iPython, Jupyter Notebooks, and GitHub.
- Excellent written communication skills.
- Bachelor’s degree in Computer Science, Statistics, Mathematics, or related; advanced degree preferred.
Application Process
Upload resume, complete a 15-minute AI interview based on your resume, and submit the form.
Key skills/competency
- Data Analysis
- SQL
- Python
- DuckDB
- pandas
- Jupyter
- Data Exploration
- Statistical Reasoning
- Business Intelligence
- Communication
How to Get Hired at Crossing Hurdles
🎯 Tips for Getting Hired
- Research Crossing Hurdles: Understand their industry and partner labs.
- Customize your resume: Highlight SQL and Python skills.
- Prepare your portfolio: Showcase data analytics projects.
- Practice technical interviews: Review data analysis case studies.
📝 Interview Preparation Advice
Technical Preparation
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Review SQL query formulation and practice.
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Brush up on Python coding exercises.
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Practice using DuckDB and pandas libraries.
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Test analytics techniques using Jupyter Notebooks.
Behavioral Questions
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Describe a challenging data problem solved.
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Explain how you manage project deadlines.
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Discuss past teamwork experience clearly.
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Share methods for handling feedback.
Frequently Asked Questions
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