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Data Scientist

Exclusive opportunity

Onsite

Data Scientist

Nexxen

Data Scientist

Skills

SQL QueriesPythonData ScienceMachine LearningScalaPySpark

1 month ago

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Important information


Contract type:

Permanent

Salary:

$160,000 – $200,000 / year

Location:

United States

Work mode:

Onsite

Published on:

13 September 2026

What they need


  • Design, implement, evaluate and help deploy machine learning models for bidding, pacing, KPI prediction (Click, Action, Viewability etc.) and Forecasting
  • Analyze large-scale behavioral and performance data using Spark (Scala/PySpark), SQL, and Python
  • Deep dive into complex, legacy codebases; you should be comfortable navigating and improving existing systems
  • Collaborate with product managers, engineers, and other data scientists to define problems and deliver end-to-end solutions
  • Write clear, concise technical documentation and communicate insights effectively across both technical and non-technical stakeholders

Benefits

  • Comprehensive health benefits
  • Flexible Time Off policy
  • Matching 401k plan
  • Commuter Benefits Plan- 5+ years of experience in a data science or applied machine learning role, ideally in a high-scale, real-time environment
  • Master’s in a quantitative field such as Data Science, Operations Research, Computer Science, Mathematics, Statistics, Industrial Engineering, Mechanical Engineering, Physics, or related field
  • Strong written and verbal communication skills — able to synthesize technical findings into clear, actionable insights
  • Self-directed, curious, and able to thrive in a fast-paced and evolving industry
  • Strong programming skills in Python, and SQL
  • Experience with Scala/Apache Spark for distributed data processing and machine learning at scale
  • Comfortable navigating large, complex legacy codebases and proposing changes to production systems. Bonus: comfortable using LLM-based tools (e.g., Copilot, ChatGPT) to accelerate development, debugging, and documentation
  • Proficient with applied machine learning techniques (classification, regression, evaluation metrics, etc.), especially tree-based models like XGBoost

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