Want to get hired at Crossing Hurdles?

Expert Data Scientist

Crossing Hurdles

HybridHybrid

Original Job Summary

About Crossing Hurdles

Crossing Hurdles is a recruitment firm that refers top candidates to leading AI research labs.

Role: Expert Data Scientist

This hourly contract role involves analyzing large structured datasets to support AI model development, designing multi-step reasoning-based analytics questions, and writing & validating SQL queries using tools like DuckDB, pandas, or Python notebooks.

Responsibilities

  • Analyze large structured datasets provided by partner organizations.
  • Design reasoning-based analytics requiring multi-step problem-solving.
  • Write and validate Snowflake SQL queries using modern data tools.
  • Produce human-readable explanations of analytical insights.
  • Format deliverables into structured JSON outputs.
  • Collaborate with peers for feedback to ensure quality.

Ideal Qualifications

  • Experience in data analytics, data science, or quantitative fields.
  • Proficiency in SQL and Python; experience with DuckDB or pandas is preferred.
  • Strong skills in data exploration, statistical reasoning, and business intelligence.
  • Experience with iPython, Jupyter Notebooks, and GitHub.
  • Excellent written communication skills to explain complex reasoning.
  • Bachelor’s degree in Computer Science, Statistics, Mathematics, or related discipline; advanced degree is a plus.

Application Process

  • Upload your resume.
  • Participate in an AI interview (15 minutes) based on your resume.
  • Submit the application form.

Key skills/competency

  • Data Analytics
  • SQL
  • Python
  • Data Exploration
  • Statistical Reasoning
  • Business Intelligence
  • Jupyter Notebooks
  • GitHub
  • DuckDB
  • Pandas

How to Get Hired at Crossing Hurdles

🎯 Tips for Getting Hired

  • Customize your resume: Tailor it to highlight relevant data analytics skills.
  • Research Crossing Hurdles: Understand their recruitment process and AI partnerships.
  • Prepare for technical questions: Brush up on SQL, Python, and data tools.
  • Practice clear communication: Demonstrate ability to explain complex insights.

📝 Interview Preparation Advice

Technical Preparation

Review SQL query optimization techniques.
Practice Python data manipulation exercises.
Familiarize with DuckDB and pandas libraries.
Test in Jupyter Notebooks environment.

Behavioral Questions

Describe teamwork in data projects.
Explain handling project feedback.
Discuss time management strategies remotely.
Showcase problem-solving under pressure.