Data Scientist – Dynamic Pricing, Offer Optimization

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November 20

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TechBiz Global

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Recruitment • Software Development • Consulting

TechBiz Global is a leading recruitment and software development company that specializes in connecting businesses with top-tier talent across 28+ countries. They serve clients from startups to major enterprises, providing expertise in hiring key roles in industries such as FinTech. In addition to talent acquisition, TechBiz Global offers comprehensive software development services to turn clients' visions into reality, powering digital transformations with expert engineers. The company also provides strategic CTO consulting services and flexible outstaffing and outsourcing solutions, helping businesses manage growth and optimize technology processes. Recognized as a top IT recruitment and consulting firm, TechBiz Global is dedicated to delivering personalized and innovative solutions to its clients, ensuring they have the tools necessary for success.

51 - 200 employees

🎯 Recruiter

📋 Description

• Develop ML models to predict customer behavior, price sensitivity, and offer conversion probability • Build and maintain elasticity models, segmentation models, and reinforcement learning frameworks • 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

• 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 • Experience with Telecom Offer & Recharge Modeling or Dynamic Pricing Systems (Nice-to-Have) • Knowledge of Pricefx PriceAI, Adobe Target Recommendations, or Reinforcement Learning frameworks (Nice-to-Have) • Understanding of Elasticity Curves, Customer Lifetime Value (CLV), and Offer Fatigue Modeling (Nice-to-Have) • Experience integrating ML outputs into business decision engines or rule systems (Nice-to-Have)

🏖️ Benefits

• Flexible working arrangements