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Siemens Digital Industries Software Senior Data Scientist- Data Strategy in Fremont, California

Siemens is a trailblazer in the EDA (Electronic Design Automation) industry providing critical technology within the semiconductor supply chain. Siemens EDA is a leader and committed to shaping the future of functional verification through data-driven innovation. We are seeking a seasoned and visionary Data Scientist to play a pivotal role in advancing our data initiatives, driving transformative insights, and leading cross-functional teams. If you are passionate about pushing the boundaries of data science and making a lasting impact, we invite you to join our dynamic team.


Data Strategy and Leadership:

  • Lead the design and development of the data strategy, aligning it with business objectives and industry trends.

  • Driving the initiative of building data assets for functional verification EDA products.

Advanced Analytics and Modeling:

  • Apply advanced analytics techniques to analyze complex and large-scale datasets to derive new product opportunities.

  • Employ predictive models and machine learning algorithms to help product team build ML products.

Cross-Functional Collaboration:

  • Collaborate closely with cross-functional teams to identify data-driven solutions to become indispensable part of the products development, marketing strategies, operational improvements, and customer insights.

  • Derive customer, operational and market insights from various data sources, and make actionable recommendations for key stakeholders to help build data driven strategy.

Leadership and Mentorship:

  • Provide mentorship and technical leadership to junior engineers, guiding their professional growth and fostering a collaborative and inclusive team environment.

  • Lead by example, exhibiting a passion for continuous learning, ethical data practices, and innovative thinking.


  1. Experience: master's degree in data science, Computer Science, Electrical Engineering, or related fields with 5+ years of data science experience; or Bachelor's degree with 7+ years of data science work experience.

  2. Advanced Analytics Techniques: Proven hands-on experience in data ingestion from complex large systems, with a track record of extracting actionable insights through data ETL and visualization.

  3. Experience with Big Data: Experience working with and extracting insights from large, complex datasets is crucial. Advanced knowledge of data lakes, data warehouses, data ETL processes, and both SQL & NoSQL databases.

  4. Machine Learning: Familiarity with a wide range of machine learning techniques, including classic ML algorithms and various neural network architectures. Experience in natural language understanding is a plus.

  5. Technical Stack: Proficiency with relevant programming languages (Python or R), data analytic tools (numpy, pandas, spark), one or more machine learning tools (scikit-learn, TensorFlow, PyTorch), data visualization tools, and one of the cloud platforms (AWS, Azure, GCP).

  6. Data strategy: Preferred experience in building and managing data assets. Strong grasp of data governance, data integrity, and best practices. Aware how data assets may impact products beyond just technical considerations.

  7. EDA Background: Preferred experience using or building EDA tools and specifically in the domain of functional verification areas including simulation, debug, coverage, static, formal or verification IP.

Additional Qualities

  1. Leadership Skills: Demonstrated leadership capabilities, including the ability to mentor junior team members, provide technical guidance, and lead projects or initiatives.

  2. Strategic Thinking: Ability to think strategically about data initiatives, aligning them with business goals, and influencing the direction of the organization's data strategy.

  3. Innovation: Ability to innovate and bring new perspectives to data science projects. Creativity in problem-solving and a willingness to explore unconventional approaches.

  4. Collaboration: Strong interpersonal skills and the ability to effectively communicate complex technical concepts to non-technical stakeholders are crucial. Ability to work effectively across cultures, teams and locations.

  5. Continuous Learning: Demonstrated commitment to continuous learning with deep understanding of computer architecture and software engineering.

  6. Project Management: Experience in managing complex data science projects from inception to deployment is valuable.

The salary range for this position is $163,600 to $261,800 and this role is eligible to earn incentive compensation. The actual compensation offered is based on the successful candidate’s work location as well as additional factors, including job-related skills, experience, and relevant education/training.Siemens offers a variety of health and wellness benefits to employees. Details regarding our benefits can be found here: In addition, this position is eligible for time off in accordance with Company policies, including paid sick leave, paid parental leave, PTO (for non-exempt employees) or non-accrued flexible vacation (for exempt employees).





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Job Family: Research & Development

Req ID: 382971