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