Senior Data Scientist

Bigabid is an innovative technology company led by data scientists and engineers devoted to mobile app growth. Our proprietary ad platform is powered by machine learning and is constantly improving its distribution algorithms.

We deliver valuable results and insights for a fast-growing clientele of major app developers using elite programmatic user acquisition and retargeting technologies.

Our ever evolving, state-of-the-art machine learning technology analyzes tens of TB of raw data per day to produce millions of ad recommendations in real-time. This data is used to power machine Learning predictions, business critical metrics, and analytics used to power our decision making process.

About the position:

We’re looking for a Senior Data Scientist to take full ownership of high-impact ML problems within our DSP platform.

You will work on core bidding, budget optimization, and prediction systems that operate at massive scale and strict latency constraints. This role combines deep modeling expertise, experimentation rigor, and strong product intuition.

You will be expected not only to build models - but to define problems, challenge assumptions, and drive measurable business impact.

What You’ll Do:

• Own end-to-end ML projects: problem definition → research → modeling → offline validation → production deployment → online A/B testing → impact analysis.
• Develop and improve models for: Bid optimization , Conversion rate / pLTV prediction, Budget pacing and allocation, Auction dynamics & win-rate modeling.
• Analyze large-scale, high-dimensional auction and user-level datasets to extract actionable insights.
• Design robust feature engineering pipelines across behavioral, contextual, and advertiser-level signals.
• Improve model performance under real-time constraints (low latency, high throughput).
• Lead experimentation design and statistical validation of online tests.
• Collaborate closely with engineering and product to translate research into scalable production systems.
  
  

• 4+ years of hands-on experience in Data Science / Machine Learning in production environments.
• Proven track record of shipping ML models that created measurable business impact.
• Experience in real-time systems, online experimentation, or large-scale optimization problems.
  
  

• Strong Python skills with ML stack (NumPy, Pandas, Scikit-learn, PyTorch/TensorFlow).
• Advanced SQL and experience working with large-scale datasets.
• Deep understanding of:
• Supervised learning (classification/regression)
• Model evaluation & calibration
• Feature engineering at scale
• Hyperparameter tuning & regularization
• Strong statistical foundation and experimental design knowledge.
  
  

• Experience in AdTech / DSP / RTB environments.
• Knowledge of auction theory or bidding strategies.
• Experience with large-scale distributed data systems (Spark, Airflow, etc.).