Associate Data Scientist - GenAI

Manulife Financial; Toronto; On-site; CAD 70,000 - 116,000; Full time

Job summary

Manulife Financial is seeking an Associate Data Scientist to develop and deploy AI/ML models, leveraging Generative AI, prompt engineering, and RAG approaches on cloud platforms such as Azure. The role involves data prep, experiments, and collaboration across data/ML teams to drive data-driven decisions across business units.

The ideal candidate has a strong ML background, experience with PyTorch and Hugging Face, and familiarity with Azure ML or Databricks.

Qualifications

• Bachelor, Master, or PhD in Computer Science, Data Science, Statistics, or related field.
• Experience as a Data Scientist with ML, generative AI, prompt engineering, and RAG apps.
• Solid understanding of ML algorithms, statistical modeling, and data analysis.

Responsibilities

• Develop and implement AI models to solve business problems using various algorithms.
• Clean, preprocess, and analyze large datasets to extract insights.
• Apply prompt engineering, build with RAG apps, and fine-tune language models.
• Collaborate with teams to define business requirements and align data science goals.
• Apply generative AI to create synthetic data and realistic simulations.
• Design experiments to validate and optimize ML models for accuracy and scalability.
• Deploy ML models on cloud platforms like Azure ML and Databricks.
• Stay updated on ML/gen AI advances and apply them to data science capabilities.
• Work with data/ML engineers to integrate solutions into systems and workflows.
• Communicate complex concepts clearly to technical and non-technical partners.

Skills

Python

ML libraries

Prompt engineering

RAG apps

LLM fine-tuning

Education

Bachelor/Master/PhD in CS/DS/Statistics

Tools

PyTorch

scikit-learn

Hugging Face

Azure ML

Databricks

Job description

We are seeking a highly skilled and motivated Associate Data Scientist to join our team. You will be responsible for developing and implementing AI and Machine Learning models, using Generative AI techniques, such as applying prompt engineering, working with RAG applications, fine-tuning LLM models, and deploying applications on cloud platforms like Azure. Your expertise in these areas will play a crucial role in driving data-driven decision-making and enhancing our business processes.

Position Responsibilities:

• Develop and implement AI models to solve complex business problems, using a variety of algorithms and techniques.
• Clean, preprocess, and analyze large datasets to extract meaningful insights and patterns.
• Apply prompt engineering techniques, build with RAG (Retrieval-Augmented Generation) applications, and fine-tune language models and improve their performance in specific tasks.
• Collaborate with multi-functional teams to identify and define business requirements, ensuring alignment with data science objectives.
• Apply generative AI techniques to generate synthetic data, create realistic simulations, and enhance data analysis capabilities.
• Design and complete experiments to validate and optimize machine learning models, ensuring accuracy, efficiency, and scalability.
• Deploy machine learning models and applications on cloud platforms like Azure ML or Databricks, ensuring seamless integration and scalability.
• Stay up-to-date with the latest advancements in machine learning, generative AI, prompt engineering, RAG applications, and cloud technologies, and apply them to enhance our data science capabilities.
• Collaborate with data engineers and ML engineers to integrate data science solutions into existing systems and workflows.
• Communicate complex technical concepts and findings to both technical and non-technical partners, ensuring clear understanding and agreement.

Required Qualifications:

• Bachelor', Master's degree, or Ph.D. in Computer Science, Data Science, Statistics, or a related field.
• Proven experience as a Data Scientist including internships or coops, with a strong focus on machine learning, generative AI, prompt engineering, and RAG applications.
• Solid understanding of machine learning algorithms, statistical modeling, and data analysis techniques.
• Proficiency in programming languages such as Python and experience with machine learning libraries/frameworks (e.g., PyTorch, scikit-learn, Hugging Face).

Preferred Qualifications:

• 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 effectively in multi-functional teams.

When you join our team:

• We’ll empower you to learn and grow the career you want.
• We’ll recognize and support you in a flexible environment where well-being and inclusion are more than just words.
• As part of our global team, we’ll support you in shaping the future you want to see.

#LI-Hybrid

The role being advertised is an existing vacancy.

About Manulife and John Hancock

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.

Manulife is an Equal Opportunity Employer

At Manulife/John Hancock, 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.

It is our priority to remove barriers to provide equal access to employment. A Human Resources representative will work with applicants who request a reasonable accommodation during the application process. All information shared during the accommodation request process will be stored and used in a manner that is consistent with applicable laws and Manulife/John Hancock policies. To request a reasonable accommodation in the application process, contact [e-mail].

Referenced Salary Location

Toronto, Ontario

Working Arrangement

Hybrid

Salary range is expected to be between

$69,525.00 CAD - $115,875.00 CAD

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. If you are applying for this role outside of the primary location, please contact [e-mail] for the salary range for your location.

Manulife offers eligible employees a wide array of customizable benefits, including health, dental, mental health, vision, short- and long-term disability, life and AD&D insurance coverage, adoption/surrogacy and wellness benefits, and employee/family assistance plans. We also offer eligible employees various retirement savings plans (including pension and a global share ownership plan with employer matching contributions) and financial education and counseling resources. Our generous paid time off program in Canada includes holidays, vacation, personal, and sick days, and we offer the full range of statutory leaves of absence. If you are applying for this role in the U.S., please contact [e-mail] for more information about U.S.-specific paid time off provisions.

We use data and analytics technologies, such as artificial intelligence (AI), and automated processing tools, to analyze and process the information you provide to us or third parties in the application process. For more information, please refer to our personal information collection statement.