Sr. Associate, Data Scientist

About the role

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. What We Value: Our Culture Our people are our most important asset, enabling Blackstone portfolio companies and investments to scale and thrive. Together, we foster a workplace where everyone can be themselves, enabling them to do their best work. At Revantage, we have exceptional people who live our values and help us pursue better every day. We offer dynamic and meaningful work, competitive compensation, benefits and flexibility. We listen and take action to ensure our organization evolves to reflect our employees' voices and support an inclusive culture. Our demonstrated commitment to our people and collaborative culture have earned us numerous awards as a top employer. Our culture is built on our shared core values and commitment to be: Learners - We learn from our challenges and successes Leaders - We commit to continuous improvement Enthusiasts - We face challenges with optimism and believe anything is possible Achievers - We expect high standards for ourselves and enable the success of our teams Partners - We deliver value and positive impact to our partners Grow your career with us. As a member of our team, you'll gain hands-on experience in the real estate industry and benefit from a supportive environment that fosters personal and professional growth. Why This Role Is Valuable 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. How You Add Value Build and deploy machine learning models to optimize revenue management and pricing strategies. Analyze large datasets to uncover insights and develop actionable recommendations for 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. What You Bring To The Role Required: 5-7 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 time series forecasting and classification, optimizing business operations and decision-making. Experience working in fast-paced environments with tight deadlines, managing multiple projects simultaneously. Demonstrated ability to work effectively within a team, producing and reviewing code written by peers. Bachelor's degree in relevant field. Technical 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: Familiarity with revenue management theory and pricing strategies is a plus. Advanced degree (master's or Ph.D.) in a relevant field is a plus. 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. Total Direct Compensation : This job is also eligible for discretionary bonus and incentive compensation on an annual basis. Benefits: The Company provid