Sr. Associate, Data Scientist

About Us

Revantage, a Blackstone Real Estate portfolio company, is a global provider of corporate services. With a corporate purpose of ‘In Pursuit of Better,’ Revantage delivers value-added services and world-class talent for Blackstone Real Estate portfolio companies, spanning diverse asset classes, including residential, logistics, office, hospitality, and retail sectors. Headquartered in Chicago, the company’s footprint extends across North America, Europe, and Asia Pacific. Rooted in a commitment to collaboration and inclusivity, Revantage goes beyond traditional corporate services and acts as a trusted partner. Across offerings that include finance, technology, human resources, and operations, Revantage proactively anticipates stakeholder needs, recruits exceptional talent, and enables its business partners to thrive.

Our people are our most important asset, enabling Blackstone portfolio companies and investments to scale and thrive. We foster a workplace where everyone can be themselves, enabling them to do their best work. Our culture is built on shared core values and a commitment to be: Learners, Leaders, Enthusiasts, Achievers, and Partners.

About the Role

The Data Scientist at Revantage will develop and deploy machine learning models to optimize revenue management and pricing strategies, analyze large datasets to generate actionable business insights, and collaborate cross-functionally to align data initiatives with company goals. This role directly impacts business operations for Blackstone Portfolio Companies by improving decision-making and operational efficiency through advanced analytics. It offers the chance to contribute to high-visibility projects that drive measurable value across the organization.

Responsibilities

• Build and deploy machine learning models to optimize revenue management and pricing strategies.
• Analyze large datasets to develop models that can drive more informed and consistent business decision-making.
• Collaborate with peers outside the data science team to align data science initiatives with business goals.
• Continuously evaluate and improve model performance through testing, tuning, and validation.
• Document processes, methodologies, and findings for both technical and non-technical audiences.

Requirements

• 3–6 years of professional experience in data science, machine learning, software engineering, or related fields, leveraging statistics and programming to drive business decisions.
• Proven expertise in building machine learning models, including predictive and forecasting models, optimizing business operations and decision-making.
• Experience working in fast-paced environments while producing rigorous, well-documented work.
• Demonstrated ability to work effectively within a team, producing and reviewing code written by peers.
• Bachelor’s degree in a relevant field, e.g., statistics, computer science, data science, etc.

Skills

• Advanced proficiency in Python, including libraries such as scikit-learn and statsmodels.
• Strong expertise in SQL for data extraction and transformation.
• Familiarity with GitLab/Azure DevOps for collaborative development and version control.
• Strong understanding of evaluation metrics and hyperparameter tuning for machine learning models.
• Solid grounding in statistics for inference and analysis.
• Familiarity with time series analysis, regression models, and econometric techniques.

Preferred Qualifications

• Familiarity with revenue management theory and pricing strategies is a plus.
• Experience in real estate finance or operations is a plus.
• Advanced degree (master’s or Ph.D.) in a relevant field is a plus.

Pay

Base Compensation Range: $123,684.00 to $164,868.00 annually. This represents the presently anticipated low and high end of the company’s base compensation range for this position. Actual base compensation range may vary based on various factors, including but not limited to location and experience. This job is also eligible for discretionary bonus and incentive compensation on an annual basis.

Benefits

• Health insurance coverage
• Retirement savings plan
• Paid holidays and paid time off (PTO)
• Hybrid work policy
• Productivity Hours – weekly meeting-free work time
• Summer Fridays
• Work From Anywhere Month
• In-house and external learning & development opportunities
• Generous wellness benefits