Senior Analytics & ML Leader — Asset Management

3M HEALTHCARE; Chicago (IL); On-site; USD 137,400 - 233,600; Full time

Benefits offered by this job

Retirement benefits

Health and welfare benefits

Paid time off

Life & accident insurance

Discretionary bonus program

Job summary

Northern Trust Asset Management seeks a Senior Analytics Specialist to advance data science initiatives across portfolio management, risk, and operations. You will build and validate AI/ML models, translate investment requirements into analytics, and present insights to senior leaders.

The role requires 7+ years in data science within asset management, with Python, R, SQL, TensorFlow/PyTorch, and hands-on with Azure, Snowflake, Databricks, and Power BI.

Qualifications

• 7+ years applying data science/AI-ML in asset management.
• Strong portfolio management, asset allocation, and risk analytics knowledge.
• Proficient in Python, R, SQL and ML frameworks.

Responsibilities

• Develop, implement, and maintain analytics models using AI/ML for portfolios, risk, and operations.
• Collaborate with investment professionals to translate requirements into analytics.
• Analyze large financial datasets to extract actionable insights.
• Build, validate, and optimize predictive models for growth and efficiency.
• Lead AI/ML governance and validation processes.
• Keep current with AI/ML and data engineering trends to enhance analytics.
• Partner with IT/Data Engineering to ensure robust data pipelines.
• Present findings clearly to technical and non-technical stakeholders.
• Mentor junior analytics team members.

Skills

Python

R

SQL

TensorFlow

PyTorch

Scikit-learn

Education

Bachelor's or Master's in Data Science/CS/Statistics/Math/Finance

Tools

Azure

Snowflake

Databricks

Power BI

Job description

Northern Trust Asset Management seeks a Senior Analytics Specialist to advance data science initiatives across portfolio management, risk, and operations. You will build and validate AI/ML models, translate investment requirements into analytics, and present insights to senior leaders.

The role requires 7+ years in data science within asset management, with Python, R, SQL, TensorFlow/PyTorch, and hands-on with Azure, Snowflake, Databricks, and Power BI.