Senior Data Scientist
About the role
We are seeking a highly skilled and motivated Senior Data Scientist – GenAI to join the Long Term Care (LTC) Fraud, Waste & Abuse (FWA) Advanced Analytics team. In this role, you will lead the design and deployment of high impact machine learning and AI solutions—combining traditional statistical modeling with advanced AI and Generative AI techniques including but not limited to generative AI techniques, such as applying prompt engineering, working with RAG applications, fine-tuning LLM models, and deploying applications on cloud platforms like Azure.
Responsibilities
- 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.
- Demonstrate proficiency in developing, fine-tuning, and deploying Generative AI models such as GPT models, as well as other innovative architectures.
- This includes understanding the nuances of model selection, optimization, and evaluation to ensure high performance and accuracy, while managing cloud-based solutions to ensure scalability, security, and performance.
- Build and optimize modular RAG (Retrieval-Augmented Generation) systems, apply advanced retrieval methods, and evaluate and monitor the performance of RAG systems.
- Apply large language models (LLMs) to parse complex documents and handle diverse layouts, such as multi-column text, tables, and images, and converting them into machine-readable formats to extract structured information.
- Stay up-to-date with the latest advancements in Generative AI, prompt engineering, Agentic Framework, and cloud technologies, to apply them and enhance our data science capabilities.
- Collaborate with data engineers and ML engineers to integrate data science solutions into existing systems and workflows.
- Communicate sophisticated technical concepts and findings to both technical and non-technical partners, ensuring clear understanding and agreement.
- Review the work of other Data Scientists and take part in model and code reviews.
- Collaborate with multi-functional teams to identify and define business requirements, ensuring alignment with data science objectives.
Requirements
- 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 in developing probabilistic models, analytics, and machine learning algorithms, including real world experience of applying analytics models, with a strong focus on machine learning, generative AI, timely engineering, and RAG applications.
- Proficiency in programming languages such as Python and experience with machine learning libraries/frameworks, e.g., PyTorch, scikit-learn, Hugging Face, SQL, graph databases (Neo4j/Cypher, Cosmos DB).
- PREFERRED: Knowledge of professional software engineering practices & standard methodologies for the full software development process, including coding standards, code reviews, source control management, build processes, testing, and operations.
- Strong collaboration and elaboration skills; demonstrates a strong commitment to organizational success; shares resources and demonstrates knowledge across the organization.
- Strong problem-solving skills and the ability to think critically and creatively to develop innovative solutions.
- Excellent communication and collaboration skills, with the ability to work optimally in multi-functional teams.
Preferred Qualifications
- Knowledge of professional software engineering practices & standard methodologies for the full software development process, including coding standards, code reviews, source control management, build processes, testing, and operations.
- Strong collaboration and elaboration skills; demonstrates a strong commitment to organizational success; shares resources and demonstrates knowledge across the organization.
- Strong problem-solving skills and the ability to think critically and creatively to develop innovative solutions.
- Excellent communication and collaboration skills, with comfort working in cross functional teams.
Benefits
Employees also have the opportunity to participate in incentive programs and earn incentive compensation tied to business and individual performance. The actual salary will vary depending on local market conditions, geography and relevant job-related factors such as knowledge, skills, qualifications, experience, and education/training.
Schedule
Hybrid
Pay
$107,450.00 USD - $199,550.00 USD
Company
Manulife Financial Corporation is a leading international financial services provider, helping people make their decisions easier and lives better. To learn more about us, visit https://www.manulife.com/en/about/our-story.html.
Equal Opportunity Employer
Manulife Financial Corporation is an Equal Opportunity Employer. We embrace our diversity. We strive to attract, develop and retain a workforce that is as diverse as the customers we serve and to foster an inclusive work environment that embraces the strength of cultures and individuals. We are committed to fair recruitment, retention, advancement and compensation, and we administer all of our practices and programs without discrimination on the basis of race, ancestry, place of origin, colour, ethnic origin, citizenship, religion or religious beliefs, creed, sex (including pregnancy and pregnancy-related conditions), sexual orientation, genetic characteristics, veteran status, gender identity, gender expression, age, marital status, family status, disability, or any other ground protected by applicable law.