Sr Data Scientist

About the role

This position requires 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.

Responsibilities

• Build and evaluate predictive models including regression, classification, time-series forecasting, and anomaly detection applied to real business problems
• Work directly with senior leaders — presenting findings with confidence, educating stakeholders on methodology, and fielding hard questions under pressure
• Accelerate analysis and automate repetitive tasks using AI tools including Claude
• Make model output and statistical findings accessible to non-technical audiences
• Hit the ground running with minimal ramp-up and deliver from day one

Requirements

• Expert-level SQL in both PostgreSQL and Snowflake, including query optimization, window functions, and complex multi-table joins across large datasets
• Proficiency in Python for data manipulation, statistical modeling, and automation — pandas, scikit-learn, and similar libraries used in practice
• 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 cloud-hosted data infrastructure, S3, and managed compute services
• 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 ramp-up and deliver from day one

Qualifications

• 4 to 8 years of experience in data science or advanced analytics
• Meaningful exposure to commercial real estate, financial services, or similarly complex transactional data environments
• Proven ability to work directly with senior leaders under pressure

Preferred

• Experience with large language model (LLM) integrations, prompt engineering, or RAG pipelines applied to document-heavy 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 Power BI 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
• 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