Sr Data Scientist - Enterprise Analytics

Venetian Las Vegas•Las Vegas, NV

13h

About The Position

The Sr Data Scientist - Enterprise Analytics leads complex analytical initiatives that support enterprise decision-making and drives the full lifecycle of data science projects, including problem definition, data exploration, model development, validation, deployment, and ongoing performance monitoring. The role turns broad or ambiguous business questions into clear analytical approaches that produce measurable impact. The position collaborates with cross-functional partners across Operations, Marketing, Finance, Revenue Management, IT, and leadership. It gathers requirements, identifies opportunities for automation and optimization, and translates analytical outcomes into recommendations for technical and nontechnical audiences. As a technical expert, the role provides thought leadership on modeling techniques, machine learning and AI methodologies, experimentation and validation, model governance, and MLOps. It also guides and mentors data scientists, strengthens team capabilities, and ensures solutions are scalable, well-designed, and aligned with long-term business strategy. The role includes 5% domestic travel for work-related conferences.

Requirements

Master’s degree or foreign equivalent in Applied Data Science, Economics, Mathematics, Statistics, or a closely related field.
At least 3 years of experience in the job offered or as a Data Scientist.
At least 3 years of experience with time series forecasting techniques, including ARIMA and Prophet, using complex, high-volume datasets.
At least 3 years of experience building, deploying, and tuning machine learning models such as Random Forest and XGBoost, and deep learning models such as CNN, RNN, LSTMs, and Transformers for structured and unstructured data.
At least 3 years of experience with exploratory data analysis, feature engineering, and statistical modeling to extract actionable insights.
At least 3 years of experience using SQL to query databases and datasets.
At least 3 years of experience with cloud platforms, including GCP, Databricks, Microsoft Azure, or AWS, and GCP tools such as BigQuery, BQ/ML, Vertex AI, and Cloud Functions for data storage, processing, and model development.
At least 3 years of experience with Python and machine learning libraries including TensorFlow, Keras, PyTorch, Scikit-learn, and XGBoost.
At least 3 years of experience with Matplotlib and Seaborn to communicate complex insights to nontechnical stakeholders.

Responsibilities

Lead complex analytical initiatives that support enterprise decision-making.
Drive data science projects through problem definition, data exploration, model development, validation, deployment, and ongoing performance monitoring.
Transform broad or ambiguous business questions into analytical approaches that produce measurable impact.
Collaborate with Operations, Marketing, Finance, Revenue Management, IT, and leadership to gather requirements and identify opportunities for automation and optimization.
Translate analytical outcomes into recommendations that technical and nontechnical audiences can understand and act on.
Provide technical thought leadership on modeling techniques, machine learning and AI methodologies, experimentation and validation, model governance, and MLOps.
Guide and mentor other data scientists and elevate the team’s technical rigor.
Ensure solutions are scalable, well-designed, and aligned with long-term business strategy.
Introduce innovative techniques, strengthen analytical capabilities, and support high-quality, data-driven organizational decisions.
Travel domestically 5% for work-related conferences.