IBM

Apptio, an IBM Company, is seeking a Staff Data Scientist to join our growing AI & Data Science team. In this senior technical leadership role, you will architect and drive cutting-edge ML and generative AI solutions that transform Apptio’s FinOps and Technology Business Management (TBM) product suite.

You’ll leverage your deep technical expertise and strategic mindset to lead projects from ideation to production, mentor team members, and shape the future of AI-driven insights for the world’s leading enterprises—empowering them to optimize cloud and IT spend with intelligent, predictive, and actionable solutions.

• Lead the vision, design, and delivery of advanced ML models and generative AI capabilities that define and differentiate Apptio’s product offerings.
• Drive AI strategy by identifying, prioritizing, and architecting high-impact ML initiatives aligned with Apptio’s product and business roadmaps.
• Own end-to-end ML workflows, from raw data ingestion and scalable feature engineering to production deployment and lifecycle management, ensuring reproducibility, robustness, and maintainability.
• Provide deep technical leadership and thought partnership to data scientists, machine learning engineers, and cross-functional teams; champion a culture of technical excellence and innovation.
• Translate ambiguous, complex business and technical challenges into well-scoped, measurable ML solutions with clear KPIs, aligned with organizational goals.
• Act as a strategic advisor to product, engineering, and executive teams, influencing decision-making on AI/ML investments, product integrations, and technology directions.
• Stay on the leading edge of AI/ML advancements, especially in generative models, NLP, large-scale ML systems, and cloud cost optimization, and proactively assess their applicability to our products.
• Promote and establish best practices in ML development, model interpretability, reproducibility, model monitoring, and responsible AI, ensuring compliance with data governance and ethical standards.

• Extensive experience in data science, applied machine learning, or related roles, with a proven track record of delivering high-impact ML solutions in production environments.
• Advanced proficiency in Python and core ML libraries (scikit-learn, pandas, NumPy) as well as deep learning frameworks such as PyTorch, TensorFlow, or Hugging Face Transformers.
• Extensive knowledge of ML algorithms, statistical modeling, and deployment of production-grade solutions at scale.
• Experience architecting ML systems working with large-scale datasets, structured and unstructured data, and cloud-native data platforms; deep SQL expertise.
• Demonstrated ability to lead complex projects, mentor senior engineers or scientists, and partner effectively with product, engineering, and executive stakeholders.
• Excellent communication skills with the ability to distill complex technical concepts for diverse audiences and drive alignment across teams.

• Experience in FinOps, cloud cost optimization, enterprise financial systems, or IT operations.
• Hands-on expertise with generative AI, LLMs, and natural language processing, including deploying or fine-tuning foundation models.
• Deep understanding of MLOps practices and tools (e.g., MLflow, SageMaker, Airflow) for managing the ML lifecycle.
• Familiarity with Apptio products (ApptioOne, Cloudability, Targetprocess) is a plus.
• Knowledge of data governance, model risk management, and responsible AI frameworks, with experience implementing them in production environments.