Data Scientist

Insight Global • Sanger, CA • 8h ago

Job Description

A reputable REIT (Real Estate Investment Trust) company is looking for hands-on, applied Data Scientists to join a growing data and analytics team supporting high-impact business initiatives across pricing, revenue management, marketing, customer analytics, website conversion, and real estate decision-making.

This is an opportunity to join a maturing analytics organization where Data Scientists will have meaningful ownership, direct business impact, and the ability to help shape best practices. The ideal candidate is not purely academic or theoretical. This person should be comfortable working across data preparation, modeling, analytics, automation, and stakeholder communication to deliver practical, scalable solutions.

Key Responsibilities

Build, improve, and deploy data science solutions that support pricing, revenue management, marketing, customer behavior, and real estate investment decisions.

Translate ambiguous business problems into data-driven approaches, models, and actionable insights.

Use Python and SQL to prepare data, develop models, validate results, and generate recommendations.

Partner with business stakeholders to understand objectives, frame analytical questions, and explain model outputs in clear business terms.

Improve existing analytical tools, models, and Excel-based processes into more scalable and production-ready solutions.

Develop machine learning models using techniques such as regression, random forest, XGBoost, and other traditional ML approaches.

Support model explainability and help non-technical users understand model logic, outputs, and business implications.

Collaborate with data engineering resources to access data, prepare datasets, and support pipelines.

Work with cloud-based tools, primarily within Google Cloud Platform.

Contribute to automation, CI/CD practices, and repeatable deployment processes for analytical and machine learning solutions.

Explore and support AI/LLM-related use cases as the organization continues to mature its AI strategy.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.

Skills and Requirements

5+ years of experience in data science, machine learning, advanced analytics, or a similar applied quantitative role.

Strong Python experience.

Strong SQL experience.

Experience building and applying machine learning or statistical models to real business problems.

Experience with traditional ML techniques such as regression, random forest, XGBoost, classification, forecasting, optimization, or similar approaches.

Ability to explain technical concepts and model outputs to non-technical stakeholders.

Experience working with messy or incomplete business requirements and shaping them into analytical solutions.

Comfort working in a smaller, collaborative, fast-moving team.

Ability to work onsite in Burbank, CA.

Preferred Skills

Google Cloud Platform experience.

Experience with pricing, revenue management, marketing analytics, customer lifetime value, web analytics, real estate analytics, retail, travel, hospitality, consumer behavior, or marketplace-style business models.

Experience productionizing models or analytical tools.

Familiarity with CI/CD, APIs, automation, or MLOps concepts.

Exposure to LLMs or AI-enabled workflows.

Experience modernizing Excel-based processes into scalable data products or models.

Experience with Jupyter Notebooks, VS Code, cloud data environments, or similar tools.

Exposure to AWS SageMaker or third-party model integration is a plus.

TensorFlow or PyTorch exposure is nice to have, but not required.

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