Data Scientist – Dynamic Pricing & Offer Optimization
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.
Highlights
Location: Remote
Department: Data & AI Engineering
Originally posted on Himalayas