Manulife/John Hancock is looking to develop and maintain machine learning and AI data pipelines to source, document, and ensure the accuracy of structured and unstructured data, and to generate actionable insights.
Requirements
Advanced Python, SQL, and deep knowledge of Gen AI libraries.
Advanced skills in data engineering, data quality, and required transforms for statistical modeling.
Advanced SQL, Snowflake, Databricks and exposure to spark.
Basic understanding of machine learning algorithms and AI toolkits.
Familiarity with statistical tests, distributions, maximum likelihood estimators, and statistical modeling techniques.
Experience developing in a DevSecOps framework, including best practices for version control, code review, unit test development, monitoring, and supporting a CI/CD framework.
Responsibilities
Develop robust ML and AI data pipelines for structured and unstructured data sets.
Assist in translating business problems into code under the guidance of senior team members.
Collaborate on feature generation for AI models.
Implement and code data science solutions in production systems.
Acquire data to measure the effectiveness of AI solutions.
Evaluate ML and AI methods relative to quantitative finance theoretical frameworks.
Develop the ability to generate actionable insights from iterative data analysis.
Other
Effective communication is essential as you'll translate data-driven outputs into business language, participate in meetings, and collaborate across teams.
Actively seek feedback and drive your career development by enhancing your technical skills.
Own career development by leveraging available resources to advance technical and business skills.
Build stable working relationships with cross-functional peers and establish a broader internal network.
Bachelor's, Master's, or PhD degree in a relevant field (not explicitly mentioned but implied)
