Senior Data Scientist – Content Engineering

Flexera

About The Position

Flexera saves customers billions of dollars in wasted technology spend. A pioneer in Hybrid ITAM and FinOps, Flexera provides award-winning, data-oriented SaaS solutions for technology value optimization (TVO), enabling IT, finance, procurement and cloud teams to gain deep insights into cost optimization, compliance and risks for each business service. Flexera One solutions are built on a set of definitive customer, supplier and industry data, powered by our Technology Intelligence Platform, that enables organizations to visualize their Enterprise Technology Blueprint™ in hybrid environments—from on-premises to SaaS to containers to cloud. We’re transforming the software industry. We’re Flexera. With more than 50,000 customers across the world, we’re achieving that goal. But we know we can’t do any of that without our team. Ready to help us re-imagine the industry during a time of substantial growth and ambitious plans? Come and see why we’re consistently recognized by Gartner, Forrester and IDC as a category leader in the marketplace. Learn more at flexera.com About the Role: We are seeking a highly skilled Senior Data Scientist to join our Content Engineering team. This role requires a strong engineering mindset combined with expertise in data science and emerging AI technologies. You will work closely with cross-functional teams to design, develop, and deploy solutions that leverage machine learning and generative AI to enhance content workflows.

Requirements

5+ years of experience in data science or related roles.
Strong programming skills in Python and familiarity with software engineering principles.
Hands-on experience with machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
Knowledge of prompt engineering and Generative AI concepts.
Understanding of CI/CD processes, testing frameworks, and collaborative development practices.
Familiarity with Databricks (nice to have).
Basic awareness of AWS concepts (e.g., S3 buckets) is a plus, though not mandatory.
Hands-on experience with Database frameworks (e.g., MySQL, PostgreSQL)
Good to have experience in tracking tools (e.g. MLflow, W&B, Neptune.ai)
Excellent problem-solving and communication skills.

Nice To Haves

Experience in data-driven automation and content workflows.
Exposure to large language models (LLMs) and agentic AI systems.
Ability to mentor junior engineers and contribute to design reviews and best practices.

Responsibilities

Design and implement machine learning models (classification and predictive models) to solve business problems.
Contribute to Generative AI initiatives, including prompt engineering, prompt validation, and optimization for agentic workflows.
Write clean, maintainable, and efficient code primarily in Python.
Collaborate within an engineering team, following best practices such as unit testing, CI/CD pipelines, code reviews, and pull requests.
Work with Databricks for data processing and model deployment (experience is a plus).
Partner with stakeholders to understand requirements and translate them into scalable solutions.
Stay updated on emerging trends in AI/ML, particularly in Generative AI and automation.