Senior Data Scientist

Manulife

. Lead end-to-end development of fraud detection and risk analytics models, including probabilistic models, anomaly detection, and ensemble approaches .

Posted 10/22/2026full-timeBoston • Massachusetts • United StatesSenior💰 $107,450 - $199,550 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Expertise in developing and deploying advanced fraud detection models and generative AI solutions, with a strong foundation in machine learning algorithms and data analytics. Proficient in collaborating with cross-functional teams to align technical solutions with business objectives.

Highest-signal resume keywords

Generative AI DevelopmentProbabilistic ModelingMachine Learning AlgorithmsPython ProficiencyCloud-Based Solutions Management

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Probabilistic ModelsAnomaly DetectionEnsemble ApproachesAdvanced ModelingAI AnalysisSQLGraph DatabasesPyTorchScikit-LearnHugging Face

Soft Skills

Technical CommunicationCollaborationReview and Feedback

Tools & Technologies

Cloud TechnologyRAG SystemsLLMsNeo4jCosmos DB

Certifications & Qualifications

Master’s DegreePh.D. Degree

Industry Keywords

Fraud DetectionRisk AnalyticsData ScienceMachine LearningPrompt Engineering

Tech Stack

Tools & technologies

CloudNeo4jPythonPyTorchScikit-LearnSQL

About the role

Key responsibilities & impact

Lead end-to-end development of fraud detection and risk analytics models, including probabilistic models, anomaly detection, and ensemble approaches
Perform advanced modeling and AI analysis on large, complex datasets to identify emerging fraud patterns and root causes
Develop, fine-tune, and deploy Generative AI models such as GPT models
Select, optimize, and evaluate models for performance and accuracy
Manage cloud-based solutions for scalability, security, and performance
Build and optimize modular RAG systems, apply advanced retrieval methods, and evaluate and monitor RAG performance
Apply LLMs to parse complex documents and diverse layouts, converting them into machine-readable formats and extracting structured information
Stay current with Generative AI, prompt engineering, Agentic Framework, and cloud technology advancements
Collaborate with data engineers and ML engineers to integrate data science solutions into existing systems and workflows
Communicate technical concepts and findings to technical and non-technical partners
Review other Data Scientists’ work and participate in model and code reviews
Collaborate with multifunctional teams to define business requirements aligned with data science objectives

Requirements

What you’ll need

Master’s or Ph.D. degree in Computer Science, Data Science, Statistics, Engineering, Physics, or a related quantitative field
5+ years of hands-on industry experience developing probabilistic models, analytics, and machine learning algorithms
Real-world experience applying analytics models, with a strong focus on machine learning, generative AI, prompt engineering, and RAG applications
Proficiency in Python
Experience with machine learning libraries/frameworks such as PyTorch, scikit-learn, and Hugging Face
Experience with SQL
Experience with graph databases such as Neo4j/Cypher and Cosmos DB

Benefits

Comp & perks

Flexible work environment
Learning and career growth opportunities
Health insurance
Dental insurance
Mental health benefits
Vision insurance
Short- and long-term disability insurance
Life and AD&D insurance coverage
Adoption/surrogacy benefits
Wellness benefits
Employee/family assistance plans
Retirement savings plans, including pension/401(k) savings plans
Global share ownership plan with employer matching contributions
Financial education and counseling resources
Up to 11 paid holidays
3 personal days
150 hours of vacation
40 hours of sick time, or more where required by law
Statutory leaves of absence
Incentive programs and incentive compensation tied to business and individual performance