Mid-Level Machine Learning & Analytics Engineer

JLL empowers you to shape a brighter way .   Our people at JLL are shaping the future of real estate for a better world by combining world class services, advisory and technology for our clients. We are committed to hiring the best, most talented people and empowering them to thrive, grow meaningful careers and to find a place where they belong.  Whether you’ve got deep experience in commercial real estate, skilled trades or technology, or you’re looking to apply your relevant experience to a new industry, join our team as we help shape a brighter way forward.

We are looking for a Mid-Level Machine Learning & Analytics Engineer to bridge the gap between predictive modeling, data architecture, and business strategy. In this role, you will design end-to-end data pipelines, build predictive and machine learning models, and create actionable analytics frameworks that drive core product decisions. You will work closely with Data Engineers, Product Managers, and Business Stakeholders to transform complex structured and unstructured data into scalable, production-grade ML models and interactive analytical tools.

Predictive & ML Modeling: Build, evaluate, and fine-tune supervised/unsupervised machine learning models (e.g., churn prediction, lifetime value estimation, recommendation engines, forecasting). Advanced Analytics & Experimentation: Design and execute A/B testing, statistical hypothesis testing, and causal inference models to evaluate product features and strategic business initiatives. Data Engineering & Pipeline Development: Construct, maintain, and optimize ETL/ELT pipelines using SQL and Python to clean, transform, and aggregate raw data into feature-ready datasets. Analytics Engineering & Business Intelligence: Model data for downstream analytics using frameworks like dbt, building high-performing data schemas (star/snowflake) and self-service BI dashboards (e.g., Tableau, Looker, Power BI). Model Deployment & Monitoring: Wrap predictive models into lightweight APIs (e.g., FastAPI) for batch or real-time inferences, setting up automated alerts for data drift, performance degradation, and pipeline failures. Cross-Functional Translation: Communicate technical methodologies, model trade-offs, and analytics insights clearly to non-technical business leaders and stakeholders. Required Qualification s 3-5 years of hands-on experience in machine learning, analytics engineering, or data science showing clear professional advancement Bachelor’s degree or Advanced Students in Computer Science, Statistics, Data Science, Mathematics, Engineering, Economics, or relevant field. Outstanding oral and written English communication skills, demonstrating a track record of articulating intricate engineering details into actionable business perspectives for diverse audiences. Practical, proven experience operationalizing and deploying ML systems within live production environments rather than relying strictly on interactive notebooks. Demonstrated experience managing feature extraction, hyperparameter optimization, model validation, and cross-validation techniques. Solid familiarity with dimensional schema architecture and modern enterprise data strategies. Location: On-site –Belen, CRI If this job description resonates with you, we encourage you to apply even if you don’t meet all of the requirements.  We’re interested in getting to know you and what you bring to the table! At JLL, we harness the power of artificial intelligence (AI) to efficiently accelerate meaningful connections between candidates and opportunities. Using AI capabilities, we analyze your application for relevant skills, experiences, and qualifications to generate valuable insights about how your unique profile aligns with the specific requirements of the role you're pursuing. JLL Privacy Notice Jones Lang LaSalle (JLL), together with its subsidiaries and affiliates, is a leading global provider of real estate and