Junior Data Scientist
@ Raw Ventures

Hybrid
$80,000
Hybrid
Full Time
Posted 21 days ago

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XXXXXXXXXX XXXXXXXXXXX XXXXXXX******* @rawventures.com
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Job Details

About the Role

The Junior Data Scientist at Raw Ventures will work on advanced data science solutions to enhance the integrity and efficiency of operations. You will develop systems for anomaly detection, fraud prevention, predictive maintenance, and customer lifecycle management.

Initially, focus will be on preprocessing, cleaning, and validating data across multiple sources, gradually moving toward taking ownership of model development, monitoring, and improvements across various applications.

Key Responsibilities

  • Data Management & Preprocessing: Collect, clean, and preprocess data from internal and external sources ensuring quality and consistency.
  • Model Development & Ownership: Design, train, validate, and own predictive models; run experiments and monitor performance.
  • Collaboration & Reporting: Work closely with the data science lead and present findings to diverse stakeholders.

Requirements

  • Essential: Strong foundation in data analysis and statistics, proficiency in Python and SQL, and experience in data visualization.
  • Nice to Have: Familiarity with gradient boosting libraries and model evaluation techniques, including SHAP values.
  • Soft Skills: Analytical curiosity, problem-solving mindset, strong communication skills, and ability to work independently.

Key skills/competency

  • Data Analysis
  • Python
  • SQL
  • Model Development
  • Anomaly Detection
  • Data Preprocessing
  • Visualization
  • Statistics
  • Collaboration
  • Communication
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How to Get Hired at Raw Ventures

🎯 Tips for Getting Hired

  • Research Raw Ventures: Review company insights on LinkedIn and Glassdoor.
  • Tailor Your Resume: Highlight data science projects and technical skills.
  • Showcase Python Expertise: Emphasize hands-on experience in Python and SQL.
  • Prepare for Technical Interviews: Practice algorithms and model evaluation discussions.

📝 Interview Preparation Advice

Technical Preparation

Practice Python coding exercises and algorithm basics.
Review SQL query optimization and data cleaning techniques.
Study model evaluation metrics and anomaly detection methods.
Experiment with data visualization using Matplotlib and Seaborn.

Behavioral Questions

Describe a time you solved data issues.
Explain handling multiple deadlines simultaneously.
Discuss resolving team communication challenges.
Share a conflict resolution experience.

Frequently Asked Questions