Senior Associate, Investment Data & AI

 

Location Designation: Hybrid - 3 days per week 

 

 

 

The Multi-Asset Solutions team at NYLIM is building an AI-enabled investment infrastructure — starting with getting our data right and growing into a platform that augments how we research, trade, and report.

 

This role sits inside the portfolio management team, not in technology. You will work directly alongside portfolio managers and trading operations professionals, developing a deep understanding of how the investment process works — and applying that understanding to help design the data structures and AI-enabled workflows that will support it in the future.

 

What You’ll Do:

1.  Build the data foundation

• Design and implement a standardized, cloud-based database architecture serving all MAS workstreams — PM research, trading & operations, and index management
• Define data structure standards across the team: how positions, trades, and performance data are named, stored, and related — creating consistency that does not currently exist
• Build data pipelines integrating external sources (Bloomberg, OMS, custodian feeds) with internal analytical and reporting tools
• Implement data validation controls and own documentation of all schemas, architecture decisions, and governance standards

 

2.  Enable AI-powered workflows

• Identify where AI tools can meaningfully improve investment workflows across PM research, trading, and reporting — and help prototype those solutions
• Ensure data infrastructure is designed AI-ready: cloud-native, well-structured, and accessible to AI tools and natural language interfaces
• Stay current on how AI is being applied in investment management and bring relevant insights back to the team
• Contribute to the governance framework for responsible AI deployment — documentation, auditability, and compliance alignment

 

3.  Drive process standardization across portfolios

• Map how each portfolio implements its daily operational processes — reconciliation, trade lifecycle, performance calculation, compliance monitoring, and reporting
• Identify where inconsistencies reflect portfolio-specific mandates (expected) versus inconsistent implementation of the same task (the opportunity)
• Propose and help implement a shared operational scaffold: a standardized daily process sequence that all portfolios follow regardless of individual investment logic

 

What You’ll Bring:

• Bachelor's degree in Computer Science, Data Science, Engineering, Statistics, Finance, or a related field
• 2–6 years of experience in data analytics, data engineering, or an analytically intensive role — asset management experience is a plus, not a requirement
• Proficiency in scripting or data languages with the ability to think programmatically and work effectively with AI coding tools
• Experience working with relational databases — able to design schemas, think through data structure, and work with structured data at scale
• Familiarity with cloud data platforms (AWS, Azure, or Google Cloud) and what it means to build and maintain data in a cloud environment
• Hands-on experience with AI or automation tools applied to real data problems — not just theoretical exposure
• Clear communicator — able to explain data concepts to non-technical colleagues and investment requirements to engineers

 

Preferred Skills:

• Familiarity with investment data: Bloomberg, OMS systems, custodian feeds, risk platforms
• Understanding of multi-asset portfolio concepts — positions, trades, benchmarks, attribution
• Experience modernizing or migrating legacy analytical workflows
• CFA progress or interest — we will actively support your development

#LI-AM1

 

Pay Transparency

Salary Range: $115,000-$164,500 

Overtime eligible: Exempt 

Discretionary bonus eligible: Yes 

Sales bonus eligible: No 

Actual base salary will be determined based on several factors but not limited to individual’s experience, skills, qualifications, and job location