Job Description
The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.
Senior Data Scientist
Company Overview
This financial technology firm is dedicated to creating a transformative ecosystem-linked financial services business in the APAC region. Led by accomplished entrepreneurs, bankers, and investors, this organization leverages over 30 years of experience in finance and technology to build innovative financial solutions that promote a more inclusive financial landscape.
Role Overview
The Senior Data Scientist will play a critical role in leading data science initiatives to drive innovation in financial technology products and services. This position requires strong expertise in machine learning, deep learning, and their applications within banking and financial services.
Key Responsibilities
- Machine Learning Model Development:
- Lead advanced model development for fraud detection, anomaly detection, recommendation engines, risk assessment, and AML systems.
- Develop credit scoring and loan automation models, customer segmentation, and market trend prediction algorithms.
- Large Language Models (LLMs):
- Implement LLMs for applications such as automated document processing, information extraction, and sentiment analysis.
- Cross-functional Collaboration:
- Partner with engineering, business, and data analytics teams to identify opportunities, define challenges, and apply data-driven solutions.
- Technical Leadership and Mentorship:
- Provide guidance to junior data scientists and lead the end-to-end machine learning pipeline, including data ingestion, preprocessing, deployment, and monitoring.
- Stay Current with Fintech AI Advances:
- Integrate new techniques and advancements in AI, particularly in fintech, into ongoing projects.
- Stakeholder Communication:
- Effectively communicate complex technical concepts to diverse audiences, including executives and stakeholders.
Requirements
- Degree in Computer Science, Statistics, Applied Mathematics, or a related quantitative field.
- Over 5 years of experience in applied data science with a focus on banking and financial services.
- Proven track record in developing and deploying machine learning models in production.
- Proficient in Python and PyData libraries (NumPy, pandas, scikit-learn).
- Experience with deep learning frameworks (PyTorch, TensorFlow).
- Familiarity with cloud platforms (AWS, GCP, or Azure) and big data technologies (Spark, Hadoop, SQL).
- Knowledge of A/B testing and experimental design in finance.
- Ability to work with structured financial data, unstructured text, and time series data.
- Strong statistical knowledge applicable to finance and excellent communication skills.
- Experience leading projects and mentoring team members.
Preferred Qualifications
- Experience with fine-tuning and deploying LLMs.
- Knowledge of MLOps practices and tools for model versioning and deployment.
- Relevant open-source projects, blogs, or conference contributions.
Disclaimer: SpringCube curates tech job listings from various company websites to support tech professionals in Singapore during these challenging times.
- No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality.
- No Client Relationship: This company is not a client of SpringCube unless stated.
- Users must click to apply, redirecting to the employer’s career page.
- No Liability: SpringCube is not liable for inaccuracies.
