Want to get hired at Crossing Hurdles?

Data Analyst

Crossing Hurdles

HybridHybrid

Original Job Summary

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

Review SQL query formulation and practice.
Brush up on Python coding exercises.
Practice using DuckDB and pandas libraries.
Test analytics techniques using Jupyter Notebooks.

Behavioral Questions

Describe a challenging data problem solved.
Explain how you manage project deadlines.
Discuss past teamwork experience clearly.
Share methods for handling feedback.