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Data scientist - dynamic pricing & offer optimization

TechBiz Global GmbH
Data Scientist
Inserat online seit: 17 März
Beschreibung

At TechBiz Global, we are providing recruitment service to our TOP clients from our portfolio. We are currently seeking a Data Scientist to join one of our clients ' teams. If you're looking for an exciting opportunity to grow in a innovative environment, this could be the perfect fit for you.


Key Responsibilities:

* Build and deploy models for:

Price Elasticity / Conversion Prediction

Churn Propensity / Retention Uplift

Segment Discovery & Similarity (Clustering, KNN)

Offer Recommendation / Ranking (Scoring Models)

* Design A/B testing and uplift modeling to evaluate campaign performance.

* Develop simulation engines for pricing what-if analysis and scenario testing.

* Create automated pipelines for model training, scoring, and retraining.

* Work closely with Data Engineers to ensure feature store alignment.

* Collaborate with the Business Decisioning team to translate insights into rules and thresholds.

* Implement feedback loops using real-time events (purchase, rejection, expiry) to improve models.

Requirements

Required Skills:

* Experience Level: 5–8 years in Applied Machine Learning, Statistical Modeling, and Data Science for large-scale systems

* Strong foundation in Machine Learning, Statistics, and Econometrics.

* Proficient in Python (pandas, scikit-learn, numpy, statsmodels, xgboost, lightGBM).

* Experience with model lifecycle management (MLOps).

* Solid understanding of telecom KPIs: ARPU, recharge frequency, wallet size, churn rate, etc.

* Ability to design feature engineering pipelines and perform A/B testing.

* Expertise in data visualization and storytelling for non-technical stakeholders

Preferred (Nice-to-Have):

* Experience with Telecom Offer & Recharge Modeling or Dynamic Pricing Systems.

* Knowledge of Pricefx PriceAI, Adobe Target Recommendations, or Reinforcement Learning frameworks.

* Understanding of Elasticity Curves, Customer Lifetime Value (CLV), and Offer Fatigue Modeling.

* Experience integrating ML outputs into business decision engines or rule systems.

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