Asks for

The ad says“Experience with Scala/Apache Spark for distributed data processing and machine learning at scale.”
The ad says“Proficient with applied machine learning techniques (classification, regression, evaluation metrics, etc.), especially tree-based models like XGBoost.”
The ad says“We’re looking for a self-directed, analytical, and curious Data Scientist II with 5+ years of hands-on experience to join our team working on the core optimization and bidding logic of the Nexxen Demand-Side Platform (DSP). You will work on problems at the intersection of machine learning, large-scale data processing, and ad delivery performance and your work will directly impact how we bid, win, and optimize impressions across real-time programmatic advertising exchanges.”
The ad says“We’re looking for a self-directed, analytical, and curious Data Scientist II with 5+ years of hands-on experience to join our team working on the core optimization and bidding logic of the Nexxen Demand-Side Platform (DSP). You will work on problems at the intersection of machine learning, large-scale data processing, and ad delivery performance and your work will directly impact how we bid, win, and optimize impressions across real-time programmatic advertising exchanges.”
The ad says“Analyze large-scale behavioral and performance data using Spark (Scala/PySpark), SQL, and Python.”
The ad says“Analyze large-scale behavioral and performance data using Spark (Scala/PySpark), SQL, and Python.”
The ad says“Proficient with applied machine learning techniques (classification, regression, evaluation metrics, etc.), especially tree-based models like XGBoost.”
The ad says“Analyze large-scale behavioral and performance data using Spark (Scala/PySpark), SQL, and Python.”
The ad says“Analyze large-scale behavioral and performance data using Spark (Scala/PySpark), SQL, and Python.”
The ad says“Analyze large-scale behavioral and performance data using Spark (Scala/PySpark), SQL, and Python.”
The ad says“Proficient with applied machine learning techniques (classification, regression, evaluation metrics, etc.), especially tree-based models like XGBoost.”

What You'll Do

We’re looking for a self-directed, analytical, and curious Data Scientist II with 5+ years of hands-on experience to join our team working on the core optimization and bidding logic of the Nexxen Demand-Side Platform (DSP). You will work on problems at the intersection of machine learning, large-scale data processing, and ad delivery performance and your work will directly impact how we bid, win, and optimize impressions across real-time programmatic advertising exchanges.

This role will be based in the New York City office. Our team follows a hybrid schedule working in-office three days a week and remotely for the rest.

Each day can be different here at Nexxen, but some of the things you can expect to be doing daily are:

Job Description

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.

What Will I Bring?

Master’s in a quantitative field such as Data Science, Operations Research, Computer Science, Mathematics, Statistics, Industrial Engineering, Mechanical Engineering, Physics, or related field

5+ years of experience in a data science or applied machine learning role, ideally in a high-scale, real-time environment.

Proficient with applied machine learning techniques (classification, regression, evaluation metrics, etc.), especially tree-based models like XGBoost.

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.

Strong programming skills in Python, and SQL.

Experience with Scala/Apache Spark for distributed data processing and machine learning at scale.

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.

In support of pay transparency and equity, the minimum and maximum full-time annual base salary for this role is $160,000 - $200,000 the time of posting, with the potential of an incentive or bonus. While this is our reasonable expectation this is not a guarantee of compensation or salary, actual compensation is influenced by a wide range of factors including but not limited to skill set, level of experience, education, certifications, responsibility, and geographic location. Candidates hired to work in other locations will be subject to the pay range associated with that location. We offer a variety of benefits, including medical, dental, vision, disability insurance, 401(k), EAP, parental leave, unlimited vacation, and company-paid holidays. The specific programs and options available will vary depending on the state, start date, and employment type. Our Talent Acquisition team will be happy to answer any questions you may have.

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