Snowflake Data Scientist

Snowflake Data Scientist Location – Richardson TX On-site ROLE OVERVIEW We are looking for Data Scientist to support the Americas Advisory Digital and Technology organization This is a hands-on high visibility engagement working directly with leadership and business stakeholders across leasing research and market intelligence You will own the full analytical stack from writing SQL to profiling raw lease data to building predictive models and AI powered solutions that surface insight leadership can act on Speed rigor and communication matter as much as technical depth WHAT YOU WILL DO Design build and validate predictive models covering lease expiry risk rent trajectory tenant retention probability and market demand signals using structured and unstructured commercial real estate data Write and optimize complex SQL queries across PostgreSQL and Snowflake to support leasing research and market intelligence teams extracting transforming and validating data at scale Analyze datasets covering lease economics property hierarchies market comparables and transaction data to answer business-critical questions with speed and accuracy Build and deploy AIassisted analytical workflows using large language models including Claude and retrievalaugmented generation RAG patterns over structured and unstructured lease document corpora Work directly with senior leaders and business stakeholders to frame data problems present model findings and translate statistical output into plainlanguage recommendations Investigate data gaps and anomalies at the field level communicate root cause clearly and coordinate with the data platform team on resolution paths Apply rigorous data testing methodology including automated data quality checks dbt SODA Great Expectations to validate analytical outputs before they reach leadership Build and maintain analytical views dashboards and documentation that business teams can trust and act on Identify patterns in data that surface risk opportunity or operational insight and frame those patterns in terms that drive leasing and market strategy decisions WHAT YOU BRING Required 4 to 8 years of experience in data science or advanced analytics with meaningful exposure to commercial real estate financial services or similarly complex transactional data environments Expertlevel SQL in both PostgreSQL and Snowflake including query optimization window functions and complex multitable joins across large datasets Proficiency in Python for data manipulation statistical modeling and automation pandas scikitlearn and similar libraries used in practice not just on a resume Hands-on experience building and evaluating predictive models regression classification timeseries forecasting and anomaly detection applied to real business problems Working knowledge of ETL and CDC concepts understanding how data flows from source systems into a cloud data warehouse and how to trace data quality issues upstream Hands-on experience with AWS or another major cloud platform Azure GCP including cloudhosted data infrastructure S3 and managed compute services Proven ability to work directly with senior leaders presenting findings with confidence educating stakeholders on methodology and fielding hard questions under pressure Proficiency with AI tools including Claude to accelerate analysis automate repetitive tasks and improve turnaround on data requests Strong written and verbal communication skills the ability to make model output and statistical findings accessible to non-technical audiences without dumbing them down High sense of urgency able to hit the ground running with minimal rampup and deliver from day one Preferred Experience with large language model LLM integrations prompt engineering or RAG pipelines applied to documentheavy analytical workflows Familiarity with commercial real estate concepts including lease structures rent schedules break clauses market comparables and transaction economics Experience with BI tools such as Sigma Computing Tableau or PowerBI for presenting model outputs and analytical dashboards Familiarity with data testing frameworks dbt tests Great Expectations or SODA and a habit of building validation into the analytical process not bolting it on afterward Background supporting advisory research or transaction services teams within a CRE or financial services organization Exposure to vector databases embedding models or semantic search applied to document retrieval WHAT SUCCESS LOOKS LIKE Leadership gets accurate wellframed answers to data questions within hours not days backed by model output or validated SQL not gut feel Predictive models surface actionable signals leases at expiry risk tenants likely to churn mar

Mandatory Skills : ETL Concepts, PostgreSQL, Python for DATA, Snowflake-Data Science