Silent Eight logo
Silent Eight

Making crime bad business

Data Scientist

Data ScientistData ScientistFull TimeRemoteSeniorTeam 51-200H1B No SponsorCompany SiteLinkedIn

Location

Singapore

Posted

62 days ago

Salary

0

Seniority

Senior

Bachelor Degree3 yrs expEnglishDockerLinuxPySparkPythonApache SparkSQL

Job Description

Data Scientist

Silent Eight

• Lead data exploration and analysis on large scale financial crime datasets — including sanctions, PEP (Politically Exposed Persons), and adverse media data — to uncover patterns, identify false positives/negatives, and drive feature improvements. • Develop and evaluate agents and rule-based models by running experiments, validating hypotheses, and fine-tuning thresholds to improve alert efficiency. • Build and deliver production-ready API integrations — coordinating with software engineers and product teams to ensure components are properly integrated, tested, and merged. • Conduct customer-focused data studies across multiple enterprise clients (e.g., financial institutions) to benchmark model performance, assess data quality, and propose data driven solutions to reduce investigation loads. • Prototype and iterate quickly — using PySpark, Jupyter notebooks, and Python to explore data, build reproducible pipelines, and generate insights that inform product decisions. • Investigate and resolve product issues in collaboration with engineering and product teams. • Contribute to R&D on emerging techniques — including graph-based approaches (GNNs, graph embeddings) for transaction monitoring, LLM-based feature exploration, and RAG-based models. • Communicate findings clearly through well-organized Jupyter notebooks, internal documentation, and stakeholder presentations, translating complex analytical results into actionable business insights.

Job Requirements

  • Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or a related field
  • Minimal 3 years of hands-on experience delivering data science projects, ideally in financial crime compliance, name screening, or AML/KYC domains
  • Strong proficiency in Python (data manipulation, modelling, pipeline development) and SQL / Spark SQL for large-scale data querying and transformation
  • Hands-on experience with PySpark or similar distributed data platforms
  • Familiarity with NLP techniques, and entity resolution concepts
  • Experience working with LLMs or RAG-based models for information extraction or classification tasks is an advantage
  • Solid understanding of data quality assessment, including profiling, anomaly identification, and merging logic across complex multi-source datasets
  • Comfortable working in Git, Docker, Linux, and collaborative development workflows (including code reviews and pull requests)
  • Strong analytical and problem-solving skills — able to investigate ambiguous data issues, form hypotheses, and validate findings rigorously
  • Good communication skills — able to document findings in a structured and reproducible manner (Jupyter notebooks, Confluence), and present results clearly to both technical and non-technical stakeholders
  • A mindset of ownership and curiosity: you take initiative, ask the right questions, and follow through to delivery.

Benefits

  • 100% remote work forever
  • Paid Development Days
  • In-house training
  • Lunch-and-learns

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