Introduction

Apptio, an IBM Company, is seeking a Data Science & Engineering Manager to lead a talented, cross-functional team of data scientists and software engineers focused on integrating advanced AI and machine learning capabilities into Apptio’s flagship FinOps and Technology Business Management (TBM) products.

In this role, you’ll provide both technical leadership and strategic direction, ensuring your team delivers innovative, production-grade AI features that help global enterprises optimize their cloud and IT investments. You’ll act as a bridge between data science, software engineering, and product management—driving execution while fostering a collaborative, high-performance culture.

Your Role And Responsibilities

• Lead, mentor, and grow a multidisciplinary team of data scientists, ML engineers, and software developers
• Define technical direction, set priorities, and drive successful execution of AI/ML projects within the product suite
• Collaborate with product and design teams to shape intelligent, customer-focused solutions
• Oversee the full AI/ML development lifecycle, from research and prototyping to scalable deployment and monitoring
• Promote best practices in machine learning engineering, MLOps, and cloud-native software development
• Foster a culture of innovation, ownership, and continuous improvement
• Communicate strategy, progress, and impact to stakeholders across the organization
  
  

Preferred Education

None

Required Technical And Professional Expertise

• Demonstrated experience in data science, software engineering, or applied ML, with at least 2 years in a technical leadership or management role
• Proven experience delivering AI/ML-powered features in a production environment
• Strong technical foundation in machine learning, data architecture, and software engineering
• Proficiency in programming languages such as Python, Java, or Go, and hands-on experience with cloud platforms (AWS, Azure, or GCP)
• Experience managing cross-functional teams and collaborating across engineering, data, and product functions
• Excellent communication and organizational skills
  
  

Preferred Technical And Professional Experience

• Experience with FinOps, IT financial management, or tools such as ApptioOne, Cloudability, or Targetprocess
• Familiarity with MLOps tools and practices (e.g., MLflow, SageMaker, Airflow, Kubernetes)
• Exposure to generative AI or large language models (LLMs) in enterprise applications
• Track record of building high-performing teams and scaling data science efforts in a SaaS environment