The Role
Build and evaluate predictive models for complex transactional data, using advanced SQL, Python, cloud data infrastructure, and statistical methods. Trace data quality issues through ETL and CDC pipelines, communicate findings to senior leaders and nontechnical stakeholders, and use AI tools to accelerate analysis. Preferred work includes LLM, RAG, BI, data testing, vector database, and commercial real estate applications.
Summary Generated by Built In
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.
- 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, not just on a resume.
- Hands-on experience building and evaluating predictive models: regression, classification, time-series 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 cloud-hosted 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 ramp-up and deliver from day one.
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, 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.
Skills Required
- 4 to 8 years of experience in data science or advanced analytics, with exposure to commercial real estate, financial services, or similarly complex transactional data environments.
- Expert-level SQL in PostgreSQL and Snowflake, including query optimization, window functions, and complex multi-table joins.
- Proficiency in Python, pandas, scikit-learn, and similar libraries for data manipulation, statistical modeling, and automation.
- Hands-on experience building and evaluating regression, classification, time-series forecasting, and anomaly detection models.
- Working knowledge of ETL and CDC concepts, cloud data warehouses, and tracing upstream data quality issues.
- Hands-on experience with AWS or another major cloud platform, including S3 and managed compute services.
- Ability to present findings to senior leaders, explain methodology, and answer challenging questions.
- Proficiency with AI tools, including Claude, for analysis and automation.
- Strong written and verbal communication skills for explaining statistical findings to nontechnical audiences.
- Ability to work with urgency, minimal ramp-up, and deliver from day one.
- Experience with LLM integrations, prompt engineering, or RAG pipelines.
- Familiarity with commercial real estate concepts including lease structures, rent schedules, break clauses, market comparables, and transaction economics.
- Experience with Sigma Computing, Tableau, or Power BI.
- Familiarity with dbt tests, Great Expectations, or SODA data testing frameworks.
- Background supporting advisory, research, or transaction services teams in commercial real estate or financial services.
- Exposure to vector databases, embedding models, or semantic search for document retrieval.
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The Company
What We Do
Anblicks is a Cloud Data Analytics Company based out of Dallas, TX, with offices in USA, India, and Australia. Since 2004, Anblicks has been helping customers by bringing value to their data and implementing modern data architecture and advanced analytics solutions in the cloud.
