Job VC
Senior Data Scientist
Technologies
Description
Our Customer:
A fast-growing product company operating in the digital advertising space, focused on building large-scale, data-driven platforms for real-time decision-making. The company develops intelligent systems that optimize campaign performance, user targeting, and revenue generation in highly dynamic environments with massive data volumes.
Your tasks:
Design and enhance machine learning models that drive real-time bidding and campaign optimization
Analyze large-scale datasets to uncover inefficiencies and identify growth opportunities
Formulate hypotheses, run experiments, and interpret results to improve system performance
Improve targeting strategies to maximize conversion rates and traffic quality
Develop approaches for measuring true campaign impact beyond standard attribution models
Optimize resource allocation strategies to balance exploration and performance
Detect anomalies and improve traffic quality through data-driven techniques
Collaborate closely with cross-functional teams to deliver scalable ML solutions
Required experience and skills:
5+ years of experience in Data Science or Machine Learning in high-scale environments
Experience in the AdTech industry is strictly required
Strong programming skills in Python and solid experience with SQL
Hands-on experience with large datasets and distributed data processing tools (e.g., Spark or similar)
Practical experience with machine learning frameworks such as PyTorch, TensorFlow, or Scikit-learn
Strong knowledge of statistics, including experimental design and causal analysis
Proven experience in running and analyzing experiments (A/B testing or similar)
Ability to understand complex systems and optimize them holistically
Strong communication skills and ability to work with both technical and non-technical stakeholders
Would be a plus:
Experience with auction-based or dynamic pricing systems
Familiarity with large-scale experimentation platforms
Understanding of budget optimization and traffic allocation strategies
Working Conditions:
Remote work
5-day
working week,
8-hour
working day
A fast-growing product company operating in the digital advertising space, focused on building large-scale, data-driven platforms for real-time decision-making. The company develops intelligent systems that optimize campaign performance, user targeting, and revenue generation in highly dynamic environments with massive data volumes.
Your tasks:
Design and enhance machine learning models that drive real-time bidding and campaign optimization
Analyze large-scale datasets to uncover inefficiencies and identify growth opportunities
Formulate hypotheses, run experiments, and interpret results to improve system performance
Improve targeting strategies to maximize conversion rates and traffic quality
Develop approaches for measuring true campaign impact beyond standard attribution models
Optimize resource allocation strategies to balance exploration and performance
Detect anomalies and improve traffic quality through data-driven techniques
Collaborate closely with cross-functional teams to deliver scalable ML solutions
Required experience and skills:
5+ years of experience in Data Science or Machine Learning in high-scale environments
Experience in the AdTech industry is strictly required
Strong programming skills in Python and solid experience with SQL
Hands-on experience with large datasets and distributed data processing tools (e.g., Spark or similar)
Practical experience with machine learning frameworks such as PyTorch, TensorFlow, or Scikit-learn
Strong knowledge of statistics, including experimental design and causal analysis
Proven experience in running and analyzing experiments (A/B testing or similar)
Ability to understand complex systems and optimize them holistically
Strong communication skills and ability to work with both technical and non-technical stakeholders
Would be a plus:
Experience with auction-based or dynamic pricing systems
Familiarity with large-scale experimentation platforms
Understanding of budget optimization and traffic allocation strategies
Working Conditions:
Remote work
5-day
working week,
8-hour
working day