Senior Data Scientist

Anblicks; Dallas (TX); On-site; USD 110,000 - 165,000; Full time

Job summary

Anblicks is seeking a data science professional with 4–8 years of experience, strong exposure to commercial real estate or financial services data, and advanced analytics capabilities. You will use SQL (PostgreSQL, Snowflake) and Python to build, evaluate, and deploy predictive models, then present findings to senior leaders to guide strategic decisions.

The role requires cloud experience (AWS preferred), data warehousing, and BI tool familiarity, with a track record of delivering actionable

Qualifications

• 4–8 years of experience in data science or advanced analytics with exposure to CRE or financial services data environments.
• Expert-level SQL in PostgreSQL and Snowflake with optimization and multi-table joins.
• Proficiency in Python for data manipulation, statistics, and automation.
• Hands-on experience building and evaluating predictive models (regression, classification, time-series).
• Understanding of ETL/CDC and cloud data workflows, including AWS/Azure/GCP.
• Experience with cloud-hosted data infrastructure and services (S3, compute).
• Ability to present findings to senior leaders and educate stakeholders on methods.
• Familiarity with AI tools like Claude to accelerate analysis and automation.
• Strong writing and speaking skills to explain results to non-technical audiences.
• High urgency and ability to start delivering from day one.

Responsibilities

• Present findings to senior leaders and educate stakeholders on methodology.
• Field hard questions and defend modeling choices under pressure.
• Collaborate with cross-functional teams to translate business problems into analytics solutions.
• Develop and maintain dashboards to communicate model outputs and insights.

Skills

Experience in data science/analytics

SQL proficiency

Python for data manipulation

Predictive modeling

ETL/CDC concepts

Cloud platform experience (AWS)

Stakeholder communication

AI tools (Claude)

Effective written/verbal communication

Fast delivery / urgency

Tools

PostgreSQL

Snowflake

AWS

dbt

Great Expectations

SODA

Sigma Computing/Tableau/Power BI

Job description

- 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.