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Data Scientist

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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 (MLflow or Kubeflow).
— 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 and practical experience in regression optimization (Linear Regression, Non-linear Regression, XGBoost, CatBoost, LightGBM, etc.).
— Experience in programmatic advertising.

What will you do

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

What you will get

  • Teams of people who love programming
  • Complex technical challenges with big data/high-load
  • Freedom to make your own engineering decisions and broad space for creativity
  • Modern technology stack to work with
  • Work remotely or from the office options on a flexible schedule
  • Long-lasting projects
  • Financial compensation for professional events and education
  • Opportunity to choose the equipment you like


LightAd is looking to develop a proprietary performance-oriented DSP with an embedded optimization module supporting various billing models, including CPM, CPC, and CPA. The main goal is to bring the technology in-house and receive all the benefits of owning the IP, such as:
Customization: LightAd should have full control over the functionality of the solution. The solution’s ability to meet various business needs and requirements will set LightAd apart from the competition.
Scalability: LightAd DSP should be designed to scale as the business grows and have the flexibility of adding new features and capabilities. The constraints of white-label solutions will no longer be an obstacle for the business.
Security and compliance: Owning the IP allows the implementation of robust security measures, better control over data privacy, protection against security threats, etc.
Long-term cost savings: Owning the IP leads to long-term cost savings.
LightAd wants to avoid ongoing licensing fees and dependencies on third-party providers, which can become significant expenses over time.
Potential acquisition: The technology should be the valuation multiplier if LightAd considers going to the business scenario.


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