Job Details

We are looking for a Data Scientist to deliver actionable insights and AI-driven enhancements across the Software Development Lifecycle (SDLC). This role combines data science, telemetry analytics, and GenAI innovation to measure SDLC health, validate pilot outcomes, and drive continuous improvement in developer productivity and platform performance.

You'll build analytics and machine learning models that surface meaningful metrics, detect anomalies, and operationalize GenAI solutions-such as automated testing, code summarization, and intelligent code suggestions-within the development lifecycle.

Key Responsibilities

• Define and implement SDLC metrics and instrumentation for CI/CD pipelines, incidents, and delivery KPIs.
• Develop dashboards, anomaly detection systems, and predictive models to monitor engineering efficiency and identify improvement opportunities.
• Design and evaluate GenAI-driven features (e.g., automated PR summaries, test generation, and code suggestions) to enhance developer workflows.
• Conduct pilot experiments, analyze outcomes, and validate model performance through data-driven evaluation frameworks.
• Collaborate with engineering, SRE, and platform teams to operationalize models, integrate analytics into CI/CD pipelines, and ensure data quality, observability, and governance.
• Champion data-driven decision-making, transforming platform telemetry into actionable insights that guide SDLC and DevOps enhancements.

Required Qualifications

• 4+ years of hands-on experience applying data science or machine learning in production environments.
• Proven experience with GenAI/LLM technologies applied to developer workflows or DevOps automation.
• Proficiency in Python (pandas, scikit-learn), ML frameworks, SQL, and data visualization tools (e.g., Tableau, Power BI).
• Experience working with observability and telemetry data (logs, metrics, traces) and A/B testing or experimental design.
• Strong communication skills, with the ability to translate technical insights into business impact.

Preferred Qualifications

• Experience with model deployment and MLOps practices.
• Knowledge of prompt engineering and best practices for safe and effective GenAI integration.
• Familiarity with cloud-based data platforms (AWS, GCP, or Azure).
• Understanding of data governance and security within enterprise environments.

Why Join Us

Join a team shaping the next generation of AI-enabled software delivery. In this role, you'll blend analytics, machine learning, and platform intelligence to create measurable impact across engineering and product teams-helping transform how developers build, test, and ship software.