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 provides a variety of benefits to employees, including health insurance coverage, retirement savings plan, paid holidays and paid time off (PTO).

The additional total direct compensation and benefits described above are subject to the terms and conditions of any governing plans, policies, practices, agreements, or other materials or documents as in effect from time to time, including but not limited to terms and conditions regarding eligibility.

Perks for You

• Competitive salary, overall compensation, and 401(k)
• Work-life balance offerings include:
  
  • Hybrid Work Policy
  • Productivity Hours - weekly meeting-free work time
  • Summer Fridays
  • Work From Anywhere Month
• In-house and external learning & development opportunities
• Generous health insurance and wellness benefits