Senior data scientist
4 days ago
About DKatalisDKatalis 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, and London Business School.About the roleWe 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 preventionAnomaly detection in financial transactionsRecommendation engines for financial productsRisk assessment and managementCustomer segmentation and personalizationCredit scoring and loan approval automationAnti-money laundering (AML) systemsMarket trend prediction and algorithmic tradingDevelop and implement large language models (LLMs) for applications such as:Automated document processing and information extractionSentiment analysis of customer feedback and market reportsCollaborate with cross-functional teams, including engineering, business stakeholders, and data analysts to identify opportunities, define problems, and implement data-driven solutionsMentor junior data scientists and provide technical leadership to the data science teamDesign and oversee the end-to-end machine learning pipeline, from data ingestion and preprocessing to model deployment and monitoring in production environmentsStay current with the latest advancements in AI and machine learning, particularly in the fintech space, and incorporate new techniques into our projectsCommunicate complex technical concepts to both technical and non-technical audiences, including executives and stakeholdersRequirements:Degree in Computer Science, Statistics, Applied Mathematics, or a related quantitative field5+ years of experience in applied data science, with a strong focus on the banking and financial services industryProven track record of building and deploying machine learning models into production environmentsProficiency in Python and the Py Data ecosystem (Num Py, pandas, scikit-learn)Strong experience with deep learning frameworks such as Py Torch or Tensor FlowFamiliarity with cloud platforms (AWS, GCP, or Azure) and their machine learning servicesExperience with big data technologies (e.g., Spark, Hadoop) and SQLExperience with A/B testing and experimental design in a financial contextDemonstrated ability to work with and process various data types, including structured financial data, unstructured text, and time series dataStrong understanding of statistical concepts and their applications in financeExcellent communication skills, with the ability to present complex ideas to both technical and non-technical audiencesExperience leading projects and mentoring junior team membersWhat will make you stand out:Experience with LLMs, including fine-tuning and deployment for specific use casesKnowledge of MLOps practices and tools for model versioning, deployment, and monitoringRelevant 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.#J-18808-Ljbffr
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