Data Scientist

Vantage Data Centers Management Company LLC; Denver (CO); Hybrid; USD 140,000 - 150,000; Full time

Benefits offered by this job

Medical coverage

Dental coverage

Vision coverage

Life insurance

Disability coverage

401k with company match

Paid time off

Employee assistance

Job summary

Vantage Data Centers Management Company LLC in Denver, CO is seeking a data scientist to develop predictive and prescriptive analytics for forecasting, capacity planning, energy optimization, and reliability analysis. The role partners with Operations, Engineering, Finance, and IT to embed models into enterprise workflows.

The position offers a hybrid work arrangement (3 days in-office, 2 days flexible) and a compensation package including base salary in the market range with annual bonus

Qualifications

• Bachelor’s degree in a quantitative discipline; Master’s preferred.
• 5–8+ years of data science, ML, and software engineering experience.
• Experience with full-stack AI development and deployment.
• Experience with large-scale operational/IoT datasets recommended.

Responsibilities

• Develop predictive and prescriptive models for operational forecasting and capacity planning.
• Build scalable ML pipelines that integrate with enterprise data platforms.
• Evaluate model performance and drive continuous improvement.
• Embed analytics into maintenance, incident response, and capacity forecasting workflows.
• Collaborate with cross-functional teams to align analytics with business goals.
• Ensure governance, documentation, and reproducibility of models.

Skills

Python

SQL

Time-series

Communication

Problem solving

Education

Bachelor's degree in quantitative field

Master’s degree preferred

Tools

Azure

Databricks

scikit-learn

TensorFlow

PyTorch

Job description

Build forecasting and optimization that power reliable operations. This Data Scientist role at Vantage Data Centers (Denver, CO, hybrid) develops, operationalizes, and scales predictive and prescriptive analytics to improve forecasting accuracy, optimize data center performance, and strengthen operational reliability across a rapidly expanding portfolio. You will partner with Operations, Engineering, capacity planning, finance, energy and sustainability, and global data strategy to embed analytical models into enterprise workflows.

What you’ll deliver

• High-impact analytical models that improve operational efficiency, reliability, and decision quality.
• Analytics embedded in real workflows, improving speed, accuracy, and consistency across maintenance planning, incident response, and capacity planning.
• A unified, scalable data ecosystem that supports analytics across the enterprise.
• Models you can trust, with governance, transparency, and alignment to real-world operational conditions.

Responsibilities

• Develop predictive and prescriptive models for operational forecasting, capacity planning, energy optimization, and reliability analysis.
• Find high-value analytical opportunities across Operations, Engineering, and Customer Experience.
• Build scalable machine learning pipelines that integrate with enterprise data platforms.
• Evaluate model performance and implement continuous improvement mechanisms.
• Integrate analytical models into operational workflows, including maintenance planning, incident response, and capacity forecasting.
• Identify automation opportunities and develop algorithms to streamline manual processes.
• Define analytical requirements that guide data engineering priorities for data quality and data governance.
• Partner with Data Engineering to ensure pipelines support model accuracy and reliability.
• Collaborate with Enterprise Architecture to align analytical solutions with long-term technology strategy.
• Support reduction of data silos and technical debt through disciplined data integration practices.
• Define KPIs and validation frameworks to measure model performance and business impact.
• Ensure models follow governance standards, including version control, documentation, and reproducibility.
• Partner with Operations leadership so outputs reflect real-world operational conditions.
• Strengthen the connection between model performance, operational reliability, and business outcomes.
• Perform additional duties as assigned by management.

Requirements

• Bachelor’s degree in a quantitative discipline.
• Master’s degree preferred.
• 5–8+ years of experience in data science, machine learning, and software engineering.
• Experience with Full Stack AI assisted development and deployment.
• Experience working with large-scale operational, IoT, or industrial datasets strongly preferred.
• Background in predictive modeling, time-series forecasting, anomaly detection, and optimization algorithms.
• Experience with Azure and Databricks.
• Familiarity with data center operations, energy systems, or mission-critical environments preferred.
• Experience collaborating with cross-functional teams in matrixed organizations.
• Experience deploying models into production environments and integrating with enterprise systems.
• Strong proficiency in Python and SQL, plus machine learning frameworks (scikit-learn, TensorFlow, PyTorch).
• Expertise in time-series modeling, statistical analysis, and data visualization.
• Ability to translate complex analytical concepts into clear business language.
• Strong understanding of data engineering principles and model lifecycle management.
• Ability to work across Operations, Engineering, IT, and Data teams.
• Strong communication, structured problem solving, and executive-ready storytelling.
• Ability to balance analytical rigor with operational practicality.
• Travel expected up to 20%, with the possibility to increase over time as business evolves.

Tools you’ll work with

Python, SQL, scikit-learn, TensorFlow, PyTorch, Azure, Databricks.

Work setup

This role is based in Denver, CO. Following the flexible work policy, it is structured as 3 days in-office and 2 days flexible.

Compensation and benefits

Salary range: $140,000 to $150,000 base + bonus. The range is based on Colorado market data and may vary in other locations; compensation may also depend on qualifications, skills, competencies, and experience, and could fall outside the range shown.

• Medical, dental, and vision coverage
• Life and AD&D
• Short and long-term disability coverage
• Paid time off
• Employee assistance
• Participation in a 401k program with company match
• Additional voluntary benefits
• Above market total compensation package
• Comprehensive suite of health and welfare, retirement, and paid leave benefits

Physical demands and special requirements

• Reasonable accommodations may be made to enable individuals with disabilities to perform essential functions.
• Occasional standing, walking, sitting, use of hands to handle or feel objects, reaching with hands and arms, climbing stairs, balancing, stooping or kneeling, talking and hearing.
• Occasional lifting and/or moving up to 25 pounds.