Lead Data Scientist

JLL (Jones Lang LaSalle)

Quick summary

Work type: On-site
Location: Chicago, IL
Salary: $140,000–$150,000 / yr
Posted: 2 days ago
Closes: Aug 30, 2026
Nearby: 99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $168k

This role $145k

$107k most similar roles pay here $235k

This role pays less than 72% of similar roles. Most pay $135,000–$200,050 — the shaded band above. At the midpoint, this role pays about $145k versus about $168k for comparable roles.

Based on 240 similar postings.

Employer

About JLL (Jones Lang LaSalle)

JLL (Jones Lang LaSalle) is a global professional services firm specializing in real estate and investment management, providing services to buyers, sellers, tenants, landlords, investors, and developers. Industry: Commercial Real Estate Services

JLL (Jones Lang LaSalle) currently has 101 open roles on FindRole.

Listed pay typically runs $140,000–$175,000 across 59 roles with salary data.

Most-posted roles

View all roles at JLL (Jones Lang LaSalle)

At a glance

TL;DR · Lead Data Scientist

Role Posting Log in to save

The Lead Data Scientist at JLL Technologies Enterprise Analytics is a senior technical leader responsible for driving high-impact financial forecasting and AI initiatives within the company’s data strategy. This role involves leading end-to-end data science projects by understanding business needs, scoping solutions, and delivering measurable outcomes while collaborating with finance, operations, and technology stakeholders. Key responsibilities include developing advanced predictive models using modern machine learning frameworks like XGBoost, LightGBM, and Prophet, as well as leveraging generative AI and large language model capabilities to build intelligent data products. The ideal candidate has 5+ years of hands-on experience in financial forecasting and FP&A analytics, with expertise in deploying machine learning models at scale on cloud platforms such as AWS or Azure, and a strong background in MLOps practices for ensuring scalability and reliability in production environments.

Skills

AWS XGBoost LightGBM Prophet TFT MLOps CI/CD Python Azure GCP Generative AI RAG Prompt Engineering PostgreSQL Snowflake Tableau Power BI

What you'll do

Lead end-to-end data science projects to deliver measurable business outcomes.
Develop and own financial forecasting models for revenue projections and cost analysis.
Apply advanced machine learning techniques to build production-ready predictive solutions.
Design MLOps practices including model versioning, monitoring, and automated retraining pipelines.
Enhance data collection and feature engineering procedures to improve analytical systems.
Leverage generative AI capabilities to build intelligent data products and automate workflows.

What we're looking for

Over 5 years of hands-on experience in machine learning and data science.
Expertise in financial forecasting and FP&A analytics with time-series models.
Proven track record deploying ML models to production using cloud platforms.
Strong background in MLOps practices including model versioning and monitoring.
Experience working cross-functionally with Finance, Technology, and Operations teams.
Masters degree or higher in Applied Mathematics, Statistics, Data Science, etc.

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