Functionize is the world's most advanced Agentic Test Automation Platform. We're helping Fortune 500 enterprises accelerate software delivery by using AI test agents that learn, adapt, and scale — replacing brittle scripts with resilient automation. From Salesforce to Workday to modern tech stacks, we're making software testing faster, smarter, and more impactful.
The Opportunity
At Functionize, data is at the heart of our AI-powered platform. We're looking for a Director to lead our Data Science practice in building robust data infrastructure and developing machine learning models that power our intelligent testing capabilities. You'll partner closely with the VP, Engineering, and Founder/CEO to drive the technical vision for AI, Data Science, and Data Engineering at Functionize.
This is a unique opportunity to shape how AI transforms software testing at scale. You’ll be both a hands-on contributor and an inspiring leader, driving strategy while guiding a team of data scientists and engineers on our most critical initiatives.
What You'll Own
- Lead and grow a team of data scientists and data engineers, conducting regular one-on-ones, providing performance feedback, and investing in their technical and career development.
- Drive the technical vision and roadmap for data infrastructure, ML pipelines, and analytics capabilities that power our AI test agents.
- Own the architecture and execution of our data platform, including real-time data processing, feature engineering, model training pipelines, and production ML systems.
- Design and implement scalable data architectures for ingesting, processing, and analyzing testing data from our enterprise customers.
- Lead the development of machine learning models for test generation, anomaly detection, and predictive analytics.
- Establish data governance, quality standards, and monitoring practices to ensure reliable and trustworthy data products.
- Partner with product, engineering, and customer success teams to translate business needs into data solutions.
- Foster a culture of experimentation and data-driven decision-making across the organization.
- Mentor team members on best practices in data engineering, MLOps, and statistical analysis.
What Makes You a Fit
- 10+ years of professional experience in data science, data engineering, or related fields, with deep expertise in building production data systems.
- 3+ years of experience in a formal management or tech lead role, with a proven track record of successfully leading data teams.
- Strong proficiency in Python and SQL, with hands-on experience in data processing frameworks and Rust a plus.
- Direct experience building and deploying machine learning models at scale, including MLOps practices and model monitoring.
- Expertise in designing data architectures using modern data stack tools (e.g., dbt, Airflow, Databricks, Snowflake).
- Deep understanding of distributed systems, data warehousing, and real-time data processing.
- Experience with cloud platforms (ideally GCP) and containerized environments (Docker, Kubernetes).
- Strong foundation in statistics, experimental design, and A/B testing methodologies.
- Track record of translating complex technical concepts for non-technical stakeholders.
- Experience with time-series data, anomaly detection, or NLP is a plus.
Featured benefits
- Medical insurance
- Vision insurance
- Dental insurance
