Data Scientist
About the role
- Experience with Python libraries such as Pandas, Scikit-learn, Keras, NLTK, and similar tools.
- Hands-on experience with LLM development frameworks such as LangChain and Semantic Kernel.
- Knowledge of relational and non-relational databases (SQL and NoSQL).Experience developing NLP solutions such as: Document Classification
- Entity Extraction
- Relationship Extraction
- Sentiment Analysis
- Understanding of: Vector databases and embeddings
- Prompt engineering
- Retrieval-Augmented Generation (RAG)
- Agentic AI and multi-agent systems
- Strong machine learning and deep learning expertise, including supervised and unsupervised techniques.
- Experience with cloud-based AI development, preferably in Microsoft Azure and Databricks environments.
- Familiarity with MLOps practices, CI/CD pipelines, automated testing, Git version control, and production deployment.
- Experience in fraud prevention, deepfake detection, healthcare analytics, EHR data, or medical terminology is an asset.
- Excellent communication and stakeholder management skills.
- Why JoinJohn Hancock?
- Work on Meaningful Problems
- Develop AI solutions that help millions of customers make better financial decisions and improve their overall experience.
- Build with Modern Technologies
- Work with LLMs, GenAI frameworks, cloud-native machine learning platforms, MLOps, and advanced AI architectures.
- Learn from a Global AI Community
- Collaborate with a network of more than 160 data scientists across John Hancock and Manulife.
- Grow Your CareerAccess continuous learning opportunities, mentorship, and exposure to innovative AI initiatives across multiple business domains.
- Thrive in an Inclusive Environment
- We're committed to fostering a workplace where everyone feels supported, valued, and empowered to do their best work.
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
It's what we read first. Occupations, seniority and locations matter more than a long history.
Two examples you can talk through
Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.
A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.
