Data Scientist | POD

Xenoss, a leading MarTech/AdTech software development house recognized among the Inc. 5000’s top 100, is seeking a visionary and accomplished Data Scientist to join our exciting new direction in data-related services. Having built custom AI-driven software solutions for industry giants like Activision Blizzard, Nestlé, and Uber, we’re leveraging our extensive experience to offer comprehensive data engineering, data analytics, data science, and AI services.

Project

We are creating a media platform that would use predictive algorithms to create optimized user journeys based on audience and content information. It should enhance the UX of branded content and raise KPIs for brand awareness and user engagement campaigns.
The technology should enable content and audience acquisition with a user journey that is seamlessly built into the content.
The product adapts to the targeted audience to drive bespoke audience journeys.
The components within the platform scope for the minimum viable product include:

• Ad Server with full dynamic creative optimization (DCO)
• Data Management functionality found in DMPs
• Various Machine learning models (provided by the Client)
• Analytics and Reporting

Required skills:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field.
• Minimum of 5 years of experience in a data science or related role, with a proven track record of applying machine learning techniques to real-world problems.
• Experience with cloud services (AWS, Azure, etc.) and ML deployment tools.
• Proficiency in Python, specifically with the classical DS stack (NumPy, SciPy, Pandas, matplotlib, scikit-learn, etc.).
• Familiarity with main Deep Learning tools and frameworks (TensorFlow/Keras, PyTorch).
• Familiarity with statistical methods and techniques, including A/B testing.
• Upper-Intermediate level of English (written and spoken).

Nice to have:

• Knowledge of modern Neural Networks architectures.
• Previous experience in Natural Language Processing or Information Retrieval.
• Working knowledge and practical experience of developing and maintaining Recommender Systems.
• Knowledge and practical experience in regression optimization (Linear Regression, Non-linear Regression, XGBoost, CatBoost, LightGBM, etc.).
• Experience in programmatic advertising.

Responsibilities:

• Work closely with the team to understand business objectives and translate them into data science initiatives.
• Design, develop, and maintain scalable solutions by using state-of-the-art AI and ML techniques.
• Establish scalable, efficient, and automated processes for data analysis and model development.
• Clearly communicate the benefits and limitations of AI/ML models and capabilities to a variety of stakeholders. Provide regular updates and insights to them.

What will you get

• The opportunity to shape the future of a leading ad tech company.
• A collaborative and dynamic work environment with a focus on innovation.
• Competitive salary and benefits package.
• High level of freedom in decision-making
• The chance to work with a talented and passionate team.