About DKatalis
DKatalis is a financial technology company with multiple offices in the APAC region. In our quest to build a better financial world, one of our key goals is to create an ecosystem-linked financial services business. DKatalis is built and backed by experienced and successful entrepreneurs, bankers, and investors in Singapore and Indonesia who have more than 30 years of financial domain experience and are from top-tier schools like Stanford, Cambridge London Business School with more than 30 years of building financial services/banking experience from Bank BTPN, Danamon, Citibank, McKinsey & Co, Northstar, Farallon Capital, and HSBC.
About the role
We are seeking an experienced Senior Data Scientist to lead our data science initiatives and drive innovation in our financial technology products and services. The ideal candidate will have a strong background in machine learning, deep learning, and their applications in the banking and financial services industry.
Key Responsibilities:
- Lead the development and implementation of advanced machine learning models for a variety of projects, including but not limited to:
- Fraud detection and prevention
- Anomaly detection in financial transactions
- Recommendation engines for financial products
- Risk assessment and management
- Customer segmentation and personalization
- Credit scoring and loan approval automation
- Anti-money laundering (AML) systems
- Market trend prediction and algorithmic trading
- Develop and implement large language models (LLMs) for applications such as:
- Automated document processing and information extraction
- Sentiment analysis of customer feedback and market reports
- Collaborate with cross-functional teams, including engineering, business stakeholders, and data analysts to identify opportunities, define problems, and implement data-driven solutions
- Mentor junior data scientists and provide technical leadership to the data science team
- Design and oversee the end-to-end machine learning pipeline, from data ingestion and preprocessing to model deployment and monitoring in production environments
- Stay current with the latest advancements in AI and machine learning, particularly in the fintech space, and incorporate new techniques into our projects
- Communicate complex technical concepts to both technical and non-technical audiences, including executives and stakeholders
Requirements:
- Degree in Computer Science, Statistics, Applied Mathematics, or a related quantitative field
- 5+ years of experience in applied data science, with a strong focus on the banking and financial services industry
- Proven track record of building and deploying machine learning models into production environments
- Proficiency in Python and the PyData ecosystem (NumPy, pandas, scikit-learn)
- Strong experience with deep learning frameworks such as PyTorch or TensorFlow
- Familiarity with cloud platforms (AWS, GCP, or Azure) and their machine learning services
- Experience with big data technologies (e.g., Spark, Hadoop) and SQL
- Experience with A/B testing and experimental design in a financial context
- Demonstrated ability to work with and process various data types, including structured financial data, unstructured text, and time series data
- Strong understanding of statistical concepts and their applications in finance
- Excellent communication skills, with the ability to present complex ideas to both technical and non-technical audiences
- Experience leading projects and mentoring junior team members
What will make you stand out:
- Experience with LLMs, including fine-tuning and deployment for specific use cases
- Knowledge of MLOps practices and tools for model versioning, deployment, and monitoring
- Relevant open-source projects, blog posts, conference talks, etc
This role offers an exciting opportunity to work at the forefront of financial technology, applying cutting-edge machine learning techniques to solve real-world problems in the banking and financial services industry. The successful candidate will play a crucial role in shaping the future of our products and services, driving innovation, and contributing to the growth of DKatalis.
