Data Scientist – Dynamic Pricing & Offer Optimization

Stack

Responsibilities

• ▹Build and deploy models for price elasticity and conversion prediction, churn and retention uplift, segment discovery and offer ranking
• ▹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 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)

Requirements

• ▹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
• ▹Ability to design feature engineering pipelines and perform A/B testing
• ▹Data visualization and storytelling for non-technical stakeholders

Nice to have

• ▹Experience with telecom offer and 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

Soft skills

What we offer

• ▹Remote work

About the company

TechBiz Global provides recruitment services to the top clients in its portfolio.