Job Title: Snowflake Data Scientist
Location: Richardson, Texas, USA (Onsite)
Job Summary
We are seeking a Snowflake Data Scientist to support the Americas Advisory Digital and Technology organization. This is a hands-on, high-visibility role working directly with leadership and business stakeholders across leasing, research, and market intelligence. The position owns the full analytical lifecycle, from SQL development and data profiling to predictive modeling and AI-powered analytical solutions that drive business decision-making.
Key Responsibilities
- Design, build, and validate predictive models for:
- Lease expiry risk
- Rent trajectory forecasting
- Tenant retention probability
- Market demand signal analysis
- Develop and optimize complex SQL queries in PostgreSQL and Snowflake.
- Extract, transform, validate, and analyze large-scale commercial real estate datasets.
- Analyze lease economics, property hierarchies, market comparables, and transaction data to answer critical business questions.
- Build and deploy AI-assisted analytical workflows using Large Language Models (LLMs), including Claude and Retrieval-Augmented Generation (RAG) patterns.
- Work directly with senior leaders and business stakeholders to define problems, present findings, and deliver actionable recommendations.
- Investigate data quality issues, identify root causes, and collaborate with data platform teams on resolution.
- Implement automated data quality validation using frameworks such as dbt, SODA, and Great Expectations.
- Build and maintain analytical views, dashboards, and documentation.
- Identify trends, risks, opportunities, and operational insights that inform leasing and market strategy decisions.
Required Skills
- Expert-level SQL in PostgreSQL and Snowflake, including:
- Query optimization
- Window functions
- Complex multi-table joins
- Strong Python skills for:
- Data manipulation
- Statistical modeling
- Process automation
- Experience with:
- Pandas
- Scikit-learn
- Similar data science libraries
- Predictive modeling expertise, including:
- Regression
- Classification
- Time-series forecasting
- Anomaly detection
- Knowledge of ETL and CDC concepts.
- Experience tracing data quality issues across cloud data ecosystems.
- Hands-on experience with AWS, Azure, or GCP, including cloud-hosted data infrastructure, S3, and managed compute services.
- Experience presenting analytical findings and methodologies to senior business stakeholders.
- Proficiency using AI tools, including Claude, to improve analytical efficiency and automate repetitive tasks.
- Strong written and verbal communication skills with the ability to explain complex analytical concepts to non-technical audiences.
Preferred Skills
- Experience with:
- Large Language Model (LLM) integrations
- Prompt engineering
- Retrieval-Augmented Generation (RAG) pipelines
- Familiarity with commercial real estate concepts, including:
- Lease structures
- Rent schedules
- Break clauses
- Market comparables
- Transaction economics
- Experience with BI platforms such as:
- Sigma Computing
- Tableau
- Power BI
- Experience with data quality and testing frameworks:
- dbt Tests
- Great Expectations
- SODA
- Background supporting advisory, research, or transaction services teams within commercial real estate or financial services organizations.
- Exposure to:
- Vector databases
- Embedding models
- Semantic search technologies
Qualifications
- Experience in data science or advanced analytics within commercial real estate, financial services, or similarly complex transactional environments.
- Ability to build, evaluate, and operationalize predictive models for real-world business applications.
- Strong understanding of cloud data platforms and modern analytics workflows.
- Ability to work independently while collaborating effectively with leadership and cross-functional teams.
- Ability to quickly understand business requirements and contribute effectively in a fast-paced environment.
We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, citizenship status, age, disability, genetic information, protected veteran status, or any other characteristic protected by applicable law.
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