Senior Data Scientist

Description

Senior Data Scientist

SNEAK PEEK

⇨ Location: Israel, hybrid

⇨ Interview process: Initial screening ⇨ take-home data challenge (labeling & scoring) ⇨ technical deep dive ⇨ HR Interview.

⇨ Contact: For questions please reach out to: [email protected]

WHO ARE WE?

At Rounds, we believe in harnessing the power of cutting-edge technology to drive business success. Our transformative, machine-learning technology identifies and optimizes mobile assets, while our team of experts, with their unparalleled human capital and business acumen, provides the strategic direction and support to turn mobile assets into profitable businesses. Together, we are revolutionizing the mobile industry. You can find out more info about us here: www.rounds.com .

THE ROLE

We seek a high-impact Senior Data Scientist to lead our intelligent lead-generation and asset-evaluation engine. You will be the primary architect transforming raw data into a streamlined onboarding funnel, directly boosting the company's bottom line.

Your core mission is to set the technical "North Star" for our modeling strategy, designing frameworks to shorten due diligence from weeks to days. This is a leadership role, deciding what to build to ensure product teams work with the most accurate, high-probability leads.

Key Opportunities

• Own the ML implementation roadmap, deciding on model architecture and deployment.
• Solve a core business challenge by automating complex due diligence via feature-based classification.
• Build a sophisticated, self-evolving system using continuous time-based learning.
• Bridge engineering and business, empowering Sales and Product teams with key logic.
  
  

• 3+ years of experience
• Expertise in developing sophisticated complex scoring mechanisms for asset quality.
• Deep understanding of time-based learning and robust drift management to maintain model integrity and accuracy.
• Ability to translate business goals into a strategic, data-driven technical roadmap that maximizes operational efficiency (e.g., reducing due diligence via feature-based automation).
• Expert-level skills in the modern machine learning ecosystem (MLOps proficiency) (e.g., Scikit-learn, XGBoost, PyTorch, TensorFlow, Pandas, BERT).
• Ability to communicate fluently in English.
  
  

• Experience working with BigQuery and understanding how to pull/clean scraped data at scale.
• Familiarity with app features and store metadata.
• Experience setting up automated pipelines for model re-training.
  
  

• Phone Screen
• Technical Interview ML Case Study (Focusing on Classification & Scoring)
• Technical Assessment
• Architecture & Strategy Interview with Head of Data Solutions and VP Data.
• HR Interview