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Data Science Engineer Jobs in Denver, CO (NOW HIRING)

Data Scientist, NA

Denver, CO · On-site

$140 - $150/hr

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 ...

Gusto is looking for an experienced Senior Data Science Leader to empower our Sales Data team, the ... Rebuild the data foundation -- alongside Data Engineering and Service Platform partners, drive the ...

Environmental Data Scientist

Boulder, CO · On-site +1

$75K - $105K/yr

Documentation & collaboration: document data schemas, analytical logic, and data sources; collaborate across the Science, Engineering, and Platform teams to keep the system understandable, accessible ...

Exceptional programming skills in Python and deep expertise in data science libraries (Scikit-learn, Pandas, NumPy, XGBoost, etc.). * Advanced SQL proficiency for querying and manipulating large ...

Data Scientist

Boulder, CO · On-site

$130K - $160K/yr

DEEP DIVE INTO THIS ROLE As a Data Scientist, you'll analyze large datasets, develop predictive models, and work with engineering teams to integrate your solutions into production.Key ...

Guide and mentor team members on advanced modeling techniques, feature engineering, and ... Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science ...

Data engineer

Denver, CO · On-site

$117K - $141K/yr

Required : • Bachelor's or Master's degree in Computer Science, Engineering, or a related field ... experience in data engineering • Strong programming skills in Python, Java, or Scala • ...

Showing results 21-40

Data Science Engineer information

See Denver, CO salary details

$45.8K

$133.5K

$182.7K

How much do data science engineer jobs pay per year?

As of Aug 17, 2026, the average yearly pay for data science engineer in Denver, CO is $133,514.00, according to ZipRecruiter salary data. Most workers in this role earn between $117,900.00 and $141,500.00 per year, depending on experience, location, and employer.

What is a data science engineer?

A Data Science Engineer is a professional who bridges the gap between data science and software engineering. They focus on designing, building, and maintaining scalable data pipelines, infrastructure, and machine learning models for production use. Their role involves data preprocessing, model deployment, performance optimization, and integrating AI solutions into applications. They work closely with data scientists, software engineers, and DevOps teams to ensure efficient data workflows.

What are the typical daily responsibilities of a data science engineer?

Data Science Engineers typically spend their days designing and building data pipelines, preparing and cleaning large datasets, and developing machine learning models to solve business problems. They work closely with data scientists, software engineers, and business stakeholders to translate requirements into scalable technical solutions. Responsibilities also include deploying models to production, monitoring their performance, and iterating on solutions based on feedback. This role offers a dynamic mix of coding, data analysis, and teamwork, making each day varied and intellectually engaging.

What are the key skills and qualifications needed to thrive in the data science engineer position, and why are they important?

A Data Science Engineer should have a strong background in statistics, machine learning, programming (typically Python or R), and data engineering, often supported by a degree in computer science, engineering, or a related field. Familiarity with data processing frameworks (like Spark or Hadoop), cloud platforms (AWS, GCP, or Azure), and certifications in data science or cloud technology are highly valued. Excellent problem-solving skills, communication abilities, and collaboration are essential soft skills for working effectively in cross-functional teams. These competencies enable Data Science Engineers to build scalable data solutions, deliver actionable insights, and drive business impact.

What does a data science engineer do?

A data science engineer designs, develops, and maintains data pipelines and infrastructure to support data analysis and machine learning models. They work with large datasets, use programming languages like Python or Scala, and often collaborate with data scientists and software engineers to implement scalable data solutions.

What are the most commonly searched types of Data Science Engineer jobs in Denver, CO?

The most popular types of Data Science Engineer jobs in Denver, CO are:

What are popular job titles related to Data Science Engineer jobs in Denver, CO?

For Data Science Engineer jobs in Denver, CO, the most frequently searched job titles are:

What job categories do people searching Data Science Engineer jobs in Denver, CO look for?

The top searched job categories for Data Science Engineer jobs in Denver, CO are:

What cities near Denver, CO are hiring for Data Science Engineer jobs?

Cities near Denver, CO with the most Data Science Engineer job openings:

Infographic showing various Data Science Engineer job openings in Denver, CO as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $133,514 per year, or $64.2 per hour.

$140 - $150/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

This job post has expired today. Applications are no longer accepted.


Job description

## Data Scientist, NAApplylocations: Denver, Coloradotime type: Full timeposted on: Posted Yesterdayjob requisition id: R22164# **About Vantage Data Centers**Vantage Data Centers powers, cools, protects and connects the technology of the world’s well-known hyperscalers, cloud providers and large enterprises. Developing and operating across North America, EMEA and Asia Pacific, Vantage has evolved data center design in innovative ways to deliver dramatic gains in reliability, efficiency and sustainability in flexible environments that can scale as quickly as the market demands.**Strategy and Transformation**The Strategy and Transformation department is a dynamic and integral component of our business strategy, dedicated to enhancing our market position, business intelligence, and insights through data analysis.**Position Overview**## **This role will be based in Denver, CO. Following our flexible work policy (3 days in-office, 2 days flexible).**The Data Scientist plays a critical role in advancing Vantage Data Centers’ analytics, automation, and data-driven decision-making capabilities across North America. This role develops, operationalizes, and scales analytical models that improve forecasting accuracy, optimize data center performance, and enhance operational reliability across Vantage’s rapidly expanding portfolio.The Data Scientist partners closely with Operations, Engineering, Capacity Planning, Finance, Energy & Sustainability, and the Global Data Strategy team to transform raw operational data into actionable insights. This role designs and deploys predictive and prescriptive models that support capacity forecasting, energy optimization, anomaly detection, asset lifecycle management, and customer experience improvements.Operating across regions and collaborating with global stakeholders, the Data Scientist ensures analytical models align with enterprise data architecture, governance standards, and long-term technology strategy. The role contributes to the evolution of Vantage’s data platform, enabling scalable analytics capabilities that support growth, reduce operational friction, and strengthen decision quality across the business.**Essential Job Functions****Data Science Strategy & Model Development*** Develop predictive and prescriptive models that support operational forecasting, capacity planning, energy optimization, and reliability analysis.* Identify 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.* Result: High-impact analytical models that improve operational efficiency, reliability, and decision quality.**Workflow Integration & Automation*** Integrate analytical models into operational workflows, including maintenance planning, incident response, and capacity forecasting.* Identify opportunities for automation and develop algorithms that streamline manual processes.* Result: Analytical capabilities embedded directly into operational workflows, improving speed, accuracy, and consistency.**Enterprise Data Alignment & System Integration*** Define analytical requirements that inform data engineering, data quality, and data governance priorities.* Partner with Data Engineering to ensure data 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.* Result: A unified data ecosystem that enables scalable, reliable analytics across the enterprise.**Performance Measurement & Model Governance*** Define KPIs and validation frameworks to measure model performance and business impact.* Ensure models adhere to governance standards, including version control, documentation, and reproducibility.* Partner with Operations leadership to ensure analytical outputs reflect real-world operational conditions.* Strengthen the linkage between model performance, operational reliability, and business outcomes.* Result: Analytical models that are trusted, transparent, and aligned with operational realities.**Additional Duties*** Handle additional duties as assigned by management.**Job 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, SQL, and 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 required is expected to be up to 20%, but may increase over time as business evolves**Physical Demands and Special Requirements**The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.While performing the duties of this job, the employee is occasionally required to stand; walk; sit; use hands to handle, or feel objects; reach with hands and arms; climb stairs; balance; stoop or kneel; talk and hear. The employee must occasionally lift and/or move up to 25 pounds.**Additional Details*** Salary Range: $140,000 - $150,000 Base + Bonus (this range is based on Colorado market data and may vary in other locations)* This position is eligible for company benefits including but not limited to 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 that includes company match, and many other additional voluntary benefits.* Compensation for the role will depend on a number of factors, including your qualifications, skills, competencies, and experience and may fall outside of the range shown.We operate with No Ego and No Arrogance. We work to build each other up and support one another, appreciating each other’s strengths and respecting each other’s weaknesses. We find joy in our work and each other, actively seeking opportunities to inject fun into what we do. Our hard and efficient work is rewarded with an above market total compensation package. We offer a comprehensive suite of health and welfare, retirement, and paid leave benefits exceeding local expectations.Throughout the year, the advantage of being part of the Vantage team is evident with an array of benefits, recognition, training and development, and the knowledge that your contribution adds value to the company and our community.Don't meet all the requirements? Please still apply if you think you are the right person for the position. We are always keen to speak to people who connect with our mission and values.Vantage Data Centers is an Equal Opportunity EmployerVantage Data Centers does not accept unsolicited resumes from search firm agencies. Fees will not be paid in the event a candidate submitted by a recruiter without an agreement in place is hired; such resumes will be deemed the sole property of Vantage Data Centers.We’ll be accepting applications for at least one week from the date this role is posted. If you're interested, we encourage you to apply soon—we’re excited to find the right person and will keep the role open until we do! #J-18808-Ljbffr