Support the development and enhancement of fraud detection and risk analytics models, including statistical models, anomaly detection, and machine learning approaches
Perform exploratory data analysis on large and complex datasets to identify fraud patterns, trends, and data quality issues
Assist in training, evaluating, and monitoring machine learning models to ensure performance and stability in production environments
Contribute to Generative AI initiatives such as prompt engineering, RAG (Retrieval‑Augmented Generation) pipelines, or document‑understanding use cases under senior guidance
Help prepare and structure data for LLM‑based applications, including extracting information from complex documents (e.g., multi‑column text, tables)
Stay curious and continue learning about advancements in machine learning, generative AI, and cloud-based analytics tools
Partner with senior data scientists, engineers, and business stakeholders to understand requirements and deliver analytical solutions
Clearly document analyses, models, and assumptions to support knowledge sharing and auditability
Communicate insights and results to both technical and non‑technical audiences with guidance and support

Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Engineering, Mathematics, or a related quantitative field
0–3 years of hands-on experience in data science, machine learning, or AI
Proficiency in Python and experience with common data science libraries (e.g., pandas, scikit learn, PyTorch, or similar)
Proficiency in SQL and relational databases; exposure to big data or cloud platforms is a plus
Familiarity with Generative AI concepts (LLMs, prompt engineering, embeddings, RAG) through coursework or projects
Experience with version control (e.g., Git) and basic software engineering best practices
Strong analytical and problem-solving skills with attention to detail
Good communication skills and the ability to work effectively in cross-functional teams
Eagerness to learn, take feedback, and grow in a collaborative environment

health insurance
dental
mental health
vision
short
and long-term disability
life and AD&D insurance coverage
adoption/surrogacy and wellness benefits
employee/family assistance plans
retirement savings plans (including pension/401(k) savings plans and a global share ownership plan with employer matching contributions)
financial education and counseling resources
generous paid time off program (including up to 11 paid holidays, 3 personal days, 150 hours of vacation, and 40 hours of sick time)
the full range of statutory leaves of absence

Associate Data Scientist

Key skills