Senior Data Scientist

Towards AI, Inc.; Denver (CO); On-site; USD 135,000 - 150,000; Full time

Job summary

bet365 in Denver, CO is seeking a Senior Data Scientist to lead the end-to-end ML lifecycle, from data prep to deployment, monitoring, and delivering measurable value across products.

You will collaborate with product and engineering teams to translate business needs into data-driven solutions, mentor teammates, and explore new methodologies to solve complex problems efficiently.

Qualifications

• PhD or MSc in a quantitative field or equivalent industry experience.
• Experience deploying and maintaining ML systems in production.
• Strong proficiency in Python, SQL and data science libraries; hands-on with GCP and MLOps.

Responsibilities

• Design, build and maintain automated pipelines for model deployment and monitoring.
• Lead end-to-end ML lifecycle to scale impact and automate business decisions.
• Mentor other team members and research new methodologies to solve complex problems.
• Partner with stakeholders to translate business needs into data science use cases.

Skills

Python

SQL

Machine Learning

ML Ops

Data Science

CI/CD

Containerization

Cloud Platforms

Leadership

Streaming Data

Education

PhD or MSc

Tools

Vertex AI

GCP

GitLab CI

BigQuery

Docker

Kubernetes

Job description

# Senior Data Scientist## bet365Published 09 Jun 2026### Share this jobDenver, CO, USA135K - 150K USD AnnualFull Time## Role Highlights### Languages usedPythonSQL### Key skillsMachine LearningML OpsData ScienceTraining ModelsComputer ScienceCICDTechnical LeadershipStreamingAutomationCloudGamingDeploymentTradingQuantitativeStatisticsDataSetsProtoTypingStorageTesting### Tools, Libraries and FrameworksVertex AIGCPGitLab CIHTTPBigQueryDockerKubernetesGKEScikit-learnPandasNumPyXGBoost## DescriptionThe role involves leading the end-to-end machine learning lifecycle to scale impact and automate business decisions. The individual will champion rapid iteration and innovation to deliver measurable value across various products. Responsibilities include designing, building, and maintaining automated pipelines for model deployment and monitoring. The position requires partnering with stakeholders to translate business needs into data science use cases. Additionally, the role involves mentoring other team members and researching new methodologies to solve complex problems efficiently.## Required Qualifications and SkillsCandidates must possess a PhD or MSc in a quantitative field or equivalent industry experience. The role requires demonstrable experience in deploying and maintaining machine learning systems in production environments. Proficiency in Python, SQL, and specific data science libraries is necessary, alongside extensive hands-on experience with Google Cloud Platform and MLOps practices. Applicants should also have a solid understanding of CI/CD principles and containerization technologies.