Data Analytics Engineer (RDSS)

Benefits

Parental leave

12 weeks From the posting source

Non-birth-parent leave

12 weeks From the posting source

Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

Not verified

Relocation assistance

Not verified

Childcare support

Not verified

Learning budget

Not verified

Verification

Source-linked checked May 7, 2026

Salary

Not verified

401(k) match

Reported from DOL Form 5500 industry filing (not employer-specific)

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Market context

U.S. role benchmark (BLS OEWS)

$111,944 U.S. median for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Data From the posting source

Seniority

Mid From the posting source

Schedule

Shift type

Not verified

Weekend work

Not verified

Company

Equity

Offered Verified - SEC 10-K source

Application

Cover letter

Not verified

Assessment

Not verified

Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Data Analytics Engineer (RDSS) Taichung Role Purpose As a leader in advanced manufacturing, Corning leverages state-of-the-art industrial data streams generated from manufacturing and process systems globally. The Data Analytics Engineer will drive the development and implementation of AI and ML solutions, transforming vast data sets into actionable manufacturing intelligence that supports Corning's Manufacturing 4.0 strategy. The position will focus on developing custom machine learning models, leveraging deep learning, NLP, and computer vision techniques to optimize manufacturing processes, enhance product quality, and introduce innovative solutions for long-term business success. The Engineer will work alongside a global, multidisciplinary team and collaborate closely with business stakeholders. Key Responsibilities Lead and execute AI/ML-driven projects in collaboration with cross-functional teams. Identify opportunities for AI/ML applications within process and product improvement initiatives. Design, prototype, and deploy predictive, prescriptive, and descriptive AI/ML solutions for critical manufacturing and business challenges. Work with stakeholders to translate complex manufacturing and business requirements into data and algorithmic problems. Cleanse, transform, and prepare large and diverse manufacturing datasets for model training and analysis. Explore and evaluate state-of-the-art ML and deep learning methods (e.g., supervised/unsupervised/reinforcement learning, LLMs, CNNs, RNNs, NLP) and apply the m

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