Senior Data Scientist

- Build and improve censored bid-landscape models to estimate clearing-price distributions from partially observed auction data

- Develop real-time win probability estimation models responsive to bid pricing dynamics

- Design and implement hierarchical lift estimation models with confidence-bound-based selection strategies

- Build conversion propensity models using sparse, delayed, and aggregate-only labels

- Develop look-alike audience modeling approaches using positive-unlabeled learning and embedding-based nearest-neighbor techniques

- Implement advertiser-level calibration strategies while independently monitoring ranking and calibration quality

- Design robust offline evaluation frameworks using inverse-propensity scoring, doubly-robust estimators, and importance reweighting

- Define exploration strategies and propensity logging approaches to ensure reliable downstream correction and evaluation

- Develop constrained optimization mechanisms for campaign objectives, pricing constraints, and volume targeting

- Contribute to data diagnostics, capability assessments, and evidence-based model recommendations

- Collaborate with the Customer team during post-launch tuning and performance validation cycles

- Prepare technical documentation and knowledge transfer materials for the Customer’s internal data science team

- Participate in architecture discussions and contribute to scalable ML platform design decisions

- 5+ years of experience in Machine Learning or Data Science with production-grade models measured against business KPIs

- Strong Python skills including numpy, pandas, and scikit-learn

- Strong SQL skills and experience working with large-scale datasets

- Deep practical experience with XGBoost, LightGBM, or CatBoost

- Strong understanding of regularization, calibration methods, and categorical feature handling

- Strong knowledge of probability, statistics, confidence intervals, and statistical power analysis

- Experience with feature engineering for structured and behavioral datasets

- Hands-on experience with Spark or PySpark

- Practical knowledge of experimentation frameworks and A/B testing methodologies

- Experience with advanced validation approaches including temporal splits, leakage detection, drift analysis, and slice-based metrics

- Understanding of explainability techniques such as SHAP and permutation importance

- Upper-Intermediate English level or higher

WILL BE A PLUS

- Experience in AdTech modeling including CTR/CVR prediction, bid-landscape modeling, audience segmentation, and RTB mechanics

- Experience working with sparse, delayed, or censored labels

- Knowledge of attribution modeling, survival analysis, and positive-unlabeled learning

- Practical experience with counterfactual and off-policy evaluation techniques

- Understanding of calibration methods including isotonic regression and Platt scaling

- Experience with hierarchical, empirical-Bayes, or partial-pooling models

- Knowledge of constrained or multi-objective optimization approaches

- Experience with uplift modeling and causal inference methods

- Experience with Vertex AI or similar managed ML training environments

- Publications, competitive modeling achievements, or open-source contributions related to Machine Learning or AdTech

PERSONAL PROFILE

- Strong analytical and problem-solving skills

- Ability to work effectively in a highly data-driven environment

- Strong communication and stakeholder management abilities

- Ability to explain complex modeling decisions to technical and non-technical audiences

- Proactive mindset with strong ownership mentality

- Attention to detail and scientific rigor in experimentation and evaluation

Join Sigma Software to help build advanced machine learning solutions for one of the large-scale players in the programmatic advertising ecosystem. We are looking for a Senior Machine Learning Engineer with strong production ML expertise and deep interest in real-time optim