Data Scientist - Hybrid

Manulife•Boston, MA

8d•$90,160 - $167,440•Hybrid

About The Position

At John Hancock, we're transforming the way people buy, manage, and benefit from life insurance. Our AI team is at the forefront of this journey, leveraging Artificial Intelligence and Generative AI to simplify customer experiences, optimize sales and marketing, strengthen fraud detection, and modernize operations. As a Data Scientist, AI & Generative AI, you'll work on high-impact initiatives that directly influence business outcomes across our U.S. Insurance business. You'll collaborate with business leaders, technology teams, and a global network of over 160 data scientists across John Hancock and Manulife, giving you exposure to world-class expertise and innovative AI applications. If you're passionate about building production-grade AI solutions, experimenting with emerging GenAI technologies, and solving complex business problems, we'd love to hear from you.

Requirements

Master's or PhD degree in Statistics, Applied Mathematics, Data Science, Computer Science, Engineering, Physics, or a related quantitative field.
2+ years of industry experience developing and deploying AI and Generative AI solutions.
Strong programming skills in Python and SQL.
Experience designing and executing data science experiments and machine learning projects.
Ability to translate business problems into scalable AI solutions.

Nice To Haves

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.

Responsibilities

Design, develop, and deploy AI and Generative AI solutions that address real business challenges.
Build and operationalize machine learning and large language model (LLM) solutions from concept through production.
Partner with business stakeholders to identify opportunities, gather requirements, formulate hypotheses, and deliver measurable outcomes.
Develop proof-of-concepts, pilot programs, and enterprise-scale AI applications.
Implement prompt engineering strategies, retrieval-augmented generation (RAG) patterns, and modern AI architectures.
Generate business insights through data exploration, experimentation, and advanced analytics.
Build scalable data pipelines and AI workflows that support production environments.
Monitor, evaluate, and continuously improve model performance and solution effectiveness.
Communicate analytical findings and technical concepts to both technical and non-technical audiences.
Stay current with emerging trends in AI, GenAI, machine learning, and cloud technologies.