Data Scientist – Hardware Validation & Test Analytics

About Centific

Centific is a frontier AI data foundry that curates diverse, high-quality data, using our purpose-built technology platforms to empower the Magnificent Seven and our enterprise clients with safe, scalable AI deployment. Our team includes more than 150 PhDs and data scientists, along with more than 4,000 AI practitioners and engineers. We harness the power of an integrated solution ecosystem—comprising industry-leading partnerships and 1.8 million vertical domain experts in more than 230 markets—to create contextual, multilingual, pre-trained datasets; fine-tuned, industry-specific LLMs; and RAG pipelines supported by vector databases. Our zero-distance innovation™ solutions for GenAI can reduce GenAI costs by up to 80% and bring solutions to market 50% faster.

Our mission is to bridge the gap between AI creators and industry leaders by bringing best practices in GenAI to unicorn innovators and enterprise customers. We aim to help these organizations unlock significant business value by deploying GenAI at scale, helping to ensure they stay at the forefront of technological advancement and maintain a competitive edge in their respective markets.

About Job

Position Summary

We are seeking a Data Scientist to support hardware validation, quality, and performance analysis for next-generation consumer devices. This position is responsible for applying statistical analysis, data modeling, machine learning techniques, and data visualization methods to large-scale testing datasets in order to identify trends, improve product quality, and support engineering decisions.

The successful candidate will work closely with engineering, testing, operations, and quality teams to analyze structured and unstructured data generated throughout the hardware development lifecycle. The role requires strong analytical skills, technical expertise in data science methodologies, and the ability to translate complex findings into actionable business and engineering recommendations.

This position requires fluency in both English and Mandarin Chinese to effectively collaborate with engineering, testing, manufacturing, and operational stakeholders across North America and China.

Key Responsibilities

• Analyze large volumes of hardware validation, reliability, performance, and operational data using statistical and analytical techniques.
• Develop predictive models, trend analyses, and analytical frameworks to identify quality risks and performance opportunities.
• Design and implement data collection, processing, and reporting methodologies for hardware testing programs.
• Apply statistical methods to evaluate test results, validate engineering hypotheses, and quantify product performance.
• Build dashboards, reports, and visualizations to communicate findings to technical and business stakeholders.
• Identify correlations, anomalies, and root causes from testing and operational datasets.
• Partner with engineering teams to define measurable quality metrics and performance indicators.
• Develop machine learning models and analytical tools that improve defect detection, risk assessment, and quality forecasting.
• Perform exploratory data analysis on structured and unstructured datasets generated by hardware testing activities.
• Work with cross-functional teams to translate business and engineering challenges into data-driven solutions.
• Present analytical findings and recommendations to leadership, engineering teams, and operational stakeholders.
• Support continuous improvement initiatives through data-driven analysis and experimentation.

Required Qualifications

• Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Information Systems, or a related quantitative discipline.
• 5+ years of professional experience in data science, advanced analytics, machine learning, statistical analysis, or related technical fields.
• Experience analyzing large-scale structured and unstructured datasets.
• Strong knowledge of probability, statistics, hypothesis testing, predictive analytics, and data modeling.
• Experience using Python, R, SQL, or similar analytical programming languages.
• Experience with machine learning frameworks and statistical analysis tools.
• Experience creating data visualizations and dashboards using tools such as Tableau, Power BI, or similar platforms.
• Proficiency in data mining, feature engineering, model development, and model validation techniques.
• Fluency in both English and Mandarin Chinese, including the ability to communicate technical analyses, research findings, and recommendations in both languages.
• Experience collaborating with technical teams located in China.
• Strong problem-solving, analytical reasoning, and communication skills.

Preferred Qualifications

• Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, Engineering, or a related quantitative field.
• Experience applying machine learning and predictive analytics to hardware testing, quality engineering, or reliability analysis.
• Experience working with consumer electronics, wearable devices, AR/VR products, or other hardware technologies.
• Experience developing automated reporting, analytical pipelines, and large-scale data processing solutions.
• Knowledge of experiment design, causal analysis, and reliability engineering concepts.
• Experience working with cloud-based data platforms and big data technologies.
• Experience supporting globally distributed engineering and testing organizations.

Annual Salary: $ 93,912

Centific is an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, ancestry, citizenship status, age, mental or physical disability, medical condition, sex (including pregnancy), gender identity or expression, sexual orientation, marital status, familial status, veteran status, or any other characteristic protected by applicable law. We consider qualified applicants regardless of criminal histories, consistent with legal requirements.