Data Scientist

Manulife

Data Scientist developing data-driven and AI-powered solutions for fraud detection at Manulife. Collaborating with teams to deploy scalable analytical solutions under senior guidance.

Posted 5/15/2026full-timeBoston • Massachusetts • 🇺🇸 United StatesJuniorMid-Level💰 $80,625 - $134,375 per yearWebsite

Tech Stack

Tools & technologies

CloudPandasPythonPyTorchSQL

About the role

Key responsibilities & impact

Contribute to the development and deployment of data-driven and AI-powered solutions that help detect fraud, protect policyholders, and improve operational efficiency
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)
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.

Requirements

What you’ll need

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.

Benefits

Comp & perks

Health insurance
Dental insurance
Mental health coverage
Vision insurance
Short- and long-term disability
Life and AD&D insurance coverage
Wellness benefits
Employee/family assistance plans
Retirement savings plans (401(k) with employer matching)
Financial education and counseling resources
Up to 11 paid holidays
3 personal days
150 hours of vacation
40 hours of sick time

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Hard Skills & Tools

data sciencemachine learningstatistical modelsanomaly detectionexploratory data analysisPythonSQLGenerative AILLMsdata preparation

Soft Skills

analytical skillsproblem-solving skillsattention to detailcommunication skillscollaborationeagerness to learnability to take feedback