A Snapshot of Your Day As Head of Data Science & MLOps, you will lead a team of data scientists and MLOps specialists in developing, deploying, and continuously improving advanced analytics and machine learning solutions. You will shape the strategic direction of Data Science and MLOps while overseeing the end-to-end lifecycle from model development and validation through production deployment and monitoring.
Working closely with business leaders, data engineering, IT, DevOps, and other stakeholders, you will translate business challenges into scalable data and AI solutions, establish robust MLOps practices, and ensure that our data-driven initiatives deliver measurable business value.
How You'll Make an Impact - Lead, develop, and mentor a team of data scientists and MLOps specialists while defining and executing the strategic vision for Data Science and MLOps in alignment with business and organizational objectives
- Oversee the development, validation, testing, deployment, and monitoring of predictive models and machine learning solutions, ensuring scalability, reliability, and performance in production environments, particularly using AWS SageMaker
- Establish and continuously improve MLOps practices across the model lifecycle, including version control, CI/CD pipelines, automated testing, model monitoring, and continuous improvement
- Collaborate with data engineering, IT, DevOps, and business teams to establish reliable data pipelines, integrate machine learning solutions into existing environments, and ensure data quality, integrity, governance, and privacy
- Partner with business leaders and stakeholders to identify high-value Data & AI opportunities, translate business needs into actionable initiatives, and communicate insights, recommendations, and outcomes to senior management
- Foster a data-driven and innovative culture by promoting experimentation, evaluating emerging Data Science, Machine Learning, and MLOps technologies, and driving the adoption of relevant methodologies and solutions
What You Bring - Bachelor's degree in Computer Science, Data Science, Statistics, or a comparable field; an advanced academic qualification or equivalent relevant experience is an advantage
- Extensive relevant professional experience in Data Science, Machine Learning, and MLOps, combined with experience leading technical teams and driving data- and AI-related initiatives
- Strong expertise in machine learning model development and production deployment, including programming languages such as Python and relevant machine learning frameworks
- Hands-on experience with cloud-based machine learning environments, particularly AWS and AWS SageMaker, including scalable deployment and operation of machine learning solutions
- Knowledge of modern MLOps practices and technologies, such as version control, CI/CD, automated testing, model monitoring, MLflow, Kubeflow, or comparable tools, as well as data governance and privacy principles. Strong analytical and problem-solving capabilities combined with effective leadership, communication, and stakeholder management skills and the ability to collaborate across technical and business functions
- Applicants must be legally authorized for employment in the United States without need for current or future employer-sponsored work authorization. Siemens Energy employees with current visa sponsorship may be eligible for internal transfers.
About the Team Gas Services Our Gas Services division offers Low-emission power generation through service and decarbonization. Zero or low emission power generation and all gas turbines under one roof, steam turbines and generators. Decarbonization opportunities through service offerings, modernization, and digitalization of the fleet.
Rewards - Career growth and development opportunities; supportive work culture
- Company paid Health and wellness benefits
- Paid Time Off and paid holidays
- 401K savings plan with company match
- Family building benefits
- Parental leave
https://jobs.siemens-energy.com/jobs
