Senior Data Scientist

Senior Data Scientist role at PT Bank Digital BCA (BCA Digital).

• Drive leadership in the Data Science team in developing and deploying predictive models for customer segmentation, churn prediction, and personalization services.
• Experience in Big Data technologies to improve scalability, real‑time analytics, and data‑driven decision‑making.
• Explore and implement AI technologies including Gen AI, LLM, and other advanced AI applications to improve operational processes and enhance customer experience.
• Design and implement ML algorithms and Auto‑ML for recommendation systems, personalized marketing, and other use cases.
• Collaborate with Data Engineering to ensure scalable data pipelines, robust data architecture, and efficient data lake/warehouse solutions.
• Perform exploratory data analysis and generate actionable insights for business stakeholders.
• Lead initiatives on advanced analytics, including NLP, conversational AI, and intelligent automation.
• Ensure compliance with data governance, security, and regulatory requirements.
• Review model flow, data flow and architecture, and understand the impact of changes to data technology that will be implemented.
• Mentor junior data scientists and contribute to building best practices in model development and deployment.
• Partner with IT and business teams to integrate models into production systems and monitor performance.

• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
• Minimum 7+ years of experience in data science roles, preferably in banking, fintech, or digital platforms.
• Proven track record of delivering machine learning and AI models in production environments.
• Strong proficiency in Python or R, and experience with ML frameworks (Tensor Flow, PyTorch, Scikit‑learn).
• Hands‑on experience with Gen AI, LLMs, and related frameworks (e.g., Hugging Face, Lang Chain).
• Expertise in Big Data technologies such as Apache Spark, Hadoop, Kafka, and distributed computing.
• Strong SQL skills and familiarity with data lake/warehouse architectures.
• Experience with cloud platforms and containerization.
• Solid understanding of data modeling, feature engineering, and model evaluation techniques.
• Knowledge of MLOps practices and tools for CI/CD in ML workflows.
• Familiarity with digital banking products, customer lifecycle, and risk management.
• Understanding of regulatory compliance in Indonesian banking.
• Ability to lead projects and mentor team members.

Mid‑Senior level

Full-time

Engineering and Information Technology

Banking