Principal Data Scientist

Job Purpose: To lead the development and deployment of advanced machine learning solutions that power personalized customer decisioning, while driving best‑in‑class modeling, MLOps, and data engineering practices. This role combines hands‑on technical expertise with leadership to deliver scalable models, robust pipelines, and high‑impact insights across the organization. What You Will Bring: Modeling Expertise : Advanced experience in building and deploying propensity models for cross-sell and upsell. Deep understanding of Next Best Action / Next Best Offer engines. Strong grasp of supervised learning, uplift modeling, and causal inference. Programming & Engineering : Expert-level coding in Python (mandatory); familiarity with R or Scala is a plus. Experience with distributed computing (Spark, Dask, Ray). Proficient in writing production-grade ML pipelines using tools like Airflow, MLflow, or Kubeflow. Strong understanding of software engineering best practices: version control, CI/CD, testing. Data Infrastructure : Experience with cloud platforms (AWS/GCP/Azure) and data warehouses (Snowflake, BigQuery, Redshift). Strong SQL skills; ability to optimize queries and manage large datasets. MLOps & Deployment : Experience deploying models to production via APIs or streaming systems (Kafka, Flink). Proficient in model versioning, experiment tracking, and deployment using MLflow, SageMaker, or Vertex AI. Monitoring & Observability: Ability to set up model monitoring, drift detection, and alerting systems using Prometheus, Grafana, Evidently, or custom dashboards. Experience with logging frameworks and performance profiling for ML services. GenAI (Preferred) : Experience with LLMs, embeddings, prompt engineering, and vector databases (e.g., FAISS, Pinecone). Ability to integrate GenAI into decisioning systems or customer-facing products. Leadership & Collaboration : Ability to lead senior data scientists while remaining hands-on. Comfortable working with product managers, engineers, and business stakeholders. What You We are Looking For: Bachelor's degree in a relevant field including Econometrics,Acturial Science.Maths/Statistics, Computer Science etc, 10 years' experience in a senior data scientist position Modelling experience including knowledge of Cloud and GenAI Strong Analytics experience in the bank sector is an advantage What’s In It for You Pay for performance culture (Competitive and performance-linked compensation) Diverse workforce and inclusive culture Career development and growth opportunities by design Work with the best minds in the field Get opportunities to bring your whole self to the organization and perform to your best.

Bachelor's degree in a relevant field (Econometrics, Actuarial Science, Maths/Statistics, Computer Science, etc.). 10 years' experience in a senior data scientist position. Modelling experience including knowledge of Cloud and GenAI. Strong analytics experience in the banking sector is an advantage.

Lead development and deployment of advanced machine learning solutions that power personalized customer decisioning, with focus on modeling, MLOps, and data engineering practices. Manage and collaborate with senior data scientists, product managers, engineers, and business stakeholders to deliver scalable models, robust pipelines, and high-impact insights across the organization.