About DKatalis

DKatalis is a financial technology company with multiple offices in the APAC region. We serve as the technological backbone for Bank Jago, an Indonesian digital bank whose mission is to drive financial inclusion by developing bespoke banking products and services that cater to a diverse customer base, from individual retail consumers to micro, small, and medium enterprises.

What sets us apart?

• Real-world Impact: Your models and analyses will directly shape bespoke banking products, influencing financial services for millions of users across Indonesia.
• Data-Rich Environment: Access vast, diverse datasets spanning individual retail consumers to micro, small, and medium enterprises (MSMEs).
• Cutting-edge Tech Stack: Leverage the latest in big data technologies, cloud computing, and machine learning frameworks.
• Cross-functional Collaboration: Work closely with product, engineering, and business teams to turn data insights into actionable strategies.

About the role

We are looking for a mid to senior-level Data Scientist with expertise in advanced modelling techniques, including knowledge graphs, recommendation systems, and fine-tuning Large Language Models (LLMs). The ideal candidate will have strong Natural Language Processing (NLP) skills to support our initiative in conversational banking and building comprehensive customer profiles.

You will work with various data types (e.g., transactional financial data, system log data, clickstream data, customer support chat logs) to help build sophisticated models that support:

• Conversational banking interfaces and chatbots
• Advanced customer profiling and personalization
• Knowledge graph construction for financial entity relationships
• Recommendation systems for financial products and services
• Digital banking product features such as AI-driven financial recommendations
• Customer segmentation and engagement analysis
• Business operations optimization
• Assisting with fraud detection and risk management functions
• Supporting the improvement of various technical operations within the business

We value candidates who are self-motivated, proactive problem-solvers with a can-do attitude. The ideal candidate demonstrates persistence and grit when facing challenges and has a track record of initiating and completing complex projects.

You will lead the delivery of data science and machine learning solutions from ideation to model development and deployment. You'll work closely with other data scientists, machine learning engineers, and product teams to drive innovation in our banking products and services.

Requirements:

Education and Background

• A Master's or Ph.D. degree in computer science, statistics, physics, mathematics, or a related field.
• Courses or certifications in finance, economics, or related disciplines are a plus.

Technical Skills

• Advanced proficiency in Python and its data science ecosystem, including tools such as Numpy, pandas, scikit-learn.
• Expertise in deep learning frameworks like PyTorch or TensorFlow.
• Experience with NLP libraries and techniques (e.g., spaCy, NLTK, transformers).
• Proficiency in building and maintaining knowledge graphs.
• Experience in developing and deploying recommendation systems.
• Familiarity with LLM fine-tuning techniques and frameworks.
• Strong version control skills (e.g., Git) and collaborative coding practices.

Knowledge and Experience

• Deep understanding of advanced statistics, machine learning concepts, and their application to real-world problems.
• 5+ years of experience working with complex machine learning models in production environments.
• Demonstrated ability to translate business problems into data science solutions.
• Experience in building conversational AI systems or chatbots.
• Familiarity with financial domain knowledge and its application in data science.

Soft Skills and Attributes

• Strong analytical and problem-solving skills.
• Excellent communication skills, both written and verbal.
• Ability to lead and mentor junior team members.
• Eagerness to stay current with the latest advancements in AI and machine learning.

Preferred Qualifications:

• Experience in the financial technology or retail banking sector.
• Active contributions to data science communities or open-source projects.
• Demonstrated thought leadership through publications, presentations, or patents.
• Expertise in big data technologies and cloud computing platforms (e.g., AWS, GCP, or Azure).

Stand-out Qualities

• Track record of implementing innovative AI solutions in fintech or related industries.
• Strong portfolio of relevant projects, particularly in NLP, knowledge graphs, or recommendation systems.
• Leadership in the data science community (organising events, giving talks, leading workshops).
• Unique skills that complement and enhance the existing Data Science team.
• Advanced understanding of cloud technologies and containerization (e.g., Docker, Kubernetes).
• Experience in ethical AI and responsible machine learning practices.