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Senior Data Scientist

Colombo • Full-time

We are Hiring - Senior Data Scientist

We are seeking a Senior Data Scientist to lead the development of high-impact Machine Learning applications that drive the bank’s core risk, revenue, and analytical strategies. This role is critical to ensuring our predictive models ranging from Credit Risk frameworks to hyper-personalization engines are robust, scalable, and integrated into the bank's digital ecosystem. 

Key Responsibilities

  • Credit Risk & Predictive Intelligence: Lead the design and deployment of production-ready Credit Risk scoring models to enhance lending precision.
  • Pattern Mining & Behavioral Analytics: Apply unsupervised learning, clustering, and association rule mining to financial data to uncover hidden spending trends and emerging customer segments.
  • Growth & Personalization Engines: Develop and optimize Next Best Action (NBA) models for upsell and cross-sell initiatives to maximize customer lifetime value.
  • Rigorous Experimentation: Design and execute A/B and multivariate tests to validate model performance and measure the incremental lift of AI-driven business interventions.
  • Agentic AI Integration: Explore and implement Agentic AI frameworks (e.g., RAG-based systems) to automate financial reasoning tasks and workflows.
  • Mentor & Guide the Data Team: Provide technical leadership, conduct code reviews, and mentor Data Scientists to ensure high engineering standards.
  • Maintain Engineering & Quality Standards: Ensure strict data governance, model monitoring, and best practices in version control and CI/CD for all ML pipelines.

Qualifications

  • Bachelor’s degree in Computer Science, Statistics, Information Technology, Engineering, or a related discipline.
  • 5+ years of hands-on Data Science or Machine Learning experience.
  • Previous experience as a Data Scientist, Senior Data Scientist, Lead Data Scientist, or Senior Machine Learning Engineer.
  • Experience in the Banking or Financial Services domain is highly desirable.

Technical Skills

  • Machine Learning & Statistical Modeling: Expert-level Python, Pandas, SQL, Spark, and Scikit-learn.
  • Deep Learning Frameworks: Proficiency in TensorFlow, PyTorch, or Keras.
  • Agentic AI: Familiarity with LangChain, LangGraph, RAG systems, and Vector Databases.
  • Data Platforms: Experience with GCP, BigQuery, Hadoop, and large-scale data environments.
  • MLOps & Infrastructure: Docker, Kubernetes, Airflow, CI/CD, model deployment, and monitoring.

Soft Skills & Leadership

  • Strong analytical and problem-solving capabilities.
  • Excellent communication skills with the ability to explain complex technical concepts to business stakeholders.
  • Attention to detail, especially in model governance, lineage, bias monitoring, and compliance.
  • Ability to lead teams, mentor junior members, and drive AI initiatives aligned with business goals.