Silicon Design Data Scientist

Join our Team

About the Opportunity

Are you ready to shape the future of verification analytics at Ericsson Silicon? Join our Design Verification Methodology team and drive cutting-edge, metric-driven methodologies across our global R&D sites in Austin, Stockholm, and Lund. As part of Ericsson Silicon, a leading engineering unit developing state-of-the-art ASICs and FPGAs for Ericsson’s 5G telecommunication portfolio, you’ll have access to vast career growth opportunities and a rich knowledge base.

In this high-impact role, you’ll combine your data science expertise with a background/ solid understanding of Hardware domain specific to ASIC IP/ASIC SoC  to develop scalable metric systems and integrate AI/ML techniques for predictive analytics. Your insights will help optimize ASIC SoC health and improve workload throughput across compute clusters and EDA tools. With your contributions, you'll drive data-driven decision-making in the verification process and play a key role in shaping the future of ASIC verification. Join us and help set new standards in this exciting field!

What you will do 

•    You will design and implement Silicon DV metric systems to track and visualize key metrics, playing a crucial role in shaping data-driven methodologies that empower silicon IP engineers, that follow: 
       a.    Coverage & Functional Coverage (pass/fail rates, closure status)
       b.    Workload Throughput (runtime, memory usage, compute efficiency, job scaling)
       c.    EDA Resource Utilization (license usage, peak load analysis, bottleneck detection)
       d.    Additional KPIs to measure and track Silicon Design and Verification status
•    Develop interactive dashboards for real-time monitoring of verification progress and EDA tool performance.
•    Create AI/ML-driven analytics for predictive workload optimization and resource allocation insights.
•    Automate data collection and transformation from EDA tools, compute clusters, and job schedulers.
•    Integrate metric systems into CI/CD workflows, enabling data-driven decision-making for IP/ASIC/SoC verification teams.
•    Collaborate with silicon engineers to improve compute scheduling, license efficiency, and verification throughput.
•    Establish best practices for data visualization, reporting, and engineering decision support.

Skills you Bring 

At least 5+ years of experience overall
•    Strong expertise in data science, analytics, and visualization tools (e.g., Python, Pandas, NumPy, Jupyter, Tableau, Grafana).
•    Experience with EDA tool monitoring (e.g., Synopsys VCS, Cadence Xcelium, Siemens Questa, JasperGold, Verdi).
•    Proficiency in SQL, NoSQL databases, and scalable data pipeline development.
•    Knowledge of AI/ML frameworks for predictive analytics in EDA workloads.
•    Familiarity with compute cluster resource monitoring (e.g., Slurm, LSF, Kubernetes).
•    Hands-on experience with runtime and memory profiling for verification workloads.
•    Understanding of CI/CD tools like Jenkins, GitLab, Docker, Kubernetes.
•    Strong programming skills in Python, Bash, Perl, or similar scripting languages.
•    Effective communication and ability to present data-driven insights to engineering teams.