Associate Data Scientist at Manulife in Boston, MA

Summary: Manulife is a leading international financial services provider, helping people make their decisions easier and lives better. We are seeking a skilled Associate Data Scientist focused on developing models leveraging conventional AI and GenAI techniques, collaborating with business teams to address their challenges and implementing AI solutions in production. Responsibilities: - Building of GenAI and AI solutions, including but not limited to analytical model development and implementation, prompt engineering, general all-purpose programming (e.g., Python), testing, communication of results, front end and back-end integration, and iterative development with clients - Collaborating with business teams to understand their business problems, gather requirements, create initial hypothesis, and development and deployment of GenAI and AI solution approach - Designing and solutioning AI/GenAI architectures (LLM/SLM/Machine learning models) to address real business problems - Leading and contributing to development of proof of concepts, pilots, and production use cases for business teams while working with cross-functional teams - Generate useful insights based on iterative data analysis and make appropriate recommendations to business partners - Continuously monitor and improve the performance of AI solutions through data analysis and testing - Strong communication to help business partners better understand the use of data, ML models, and AI solutions - Stay up-to-date with the latest trends and advancements in cloud-based machine learning platforms, technologies, and tools Required Qualifications: - Experiences in developing and deploying models using AI and GenAI techniques - Proficient in programming using Python and SQL - Master's degree or PhD degree in quantitative fields such as Statistics, Applied Mathematics, Data Science, Engineering, or Computer Science or Physics Preferred Qualifications: - Experience in using Python (e.g., Pandas, NLTK, Scikit-learn, Keras etc.), common LLM development frameworks (e.g., Langchain, Semantic Kernel), Relational storage (SQL), Non-relational storage (NoSQL) - Strong understanding of medical terminology, EHR data, and coding systems - Hands-on experience in developing models solving NLP tasks, including Document Classification, Entity Extraction, Entity Relation Extraction, etc - Hands-on experience in processing documents (PDF/Images) using vision and/or language models, as well as OCR techniques - Proven problem-solving abilities, including conducting root cause analysis to address specific business inquiries and identify opportunities for enhancement - Excellent communication skills to explain complex topics to diverse audiences - Demonstrated expertise in the data analytics life cycle, encompassing problem framing, data collection, data cleansing, insights generation, reporting, and communication - Skilled in machine learning modeling life cycle, including exploratory data analysis, data cleansing, feature engineering, model building, deployment, and monitoring - Good understanding of vectorization and embedding, prompt engineering, RAG, Multi-agent techniques - Solid knowledge and highly skilled in supervised and unsupervised machine learning algorithms, deep learning, and LLMs - Experience in developing and deploying models in cloud-based environments, specifically Microsoft Azure, and Databricks, following MLOps best practices - Experience with Git Version Control, Unit/Integration/End-to-End Testing, CI/CD, release management, etc Required Skills: AI techniques, GenAI techniques, Machine learning models, Python programming Important Skills: SQL proficiency, Data pipelines, NLP tasks, Cloud environments Benefits: Health, dental, mental health, vision, short- and long-term disability, life and AD&D insurance coverage, Adoption/surrogacy and wellness benefits, Employee/family assistance plans, Various 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 in the U.S. includes up to 11 paid holidays, 3 personal days, 150 hours of vacation, and 40 hours of sick time (or more where required by law) each year, Full range of statutory leaves of absence