A Senior Data Scientist responsible for developing and implementing statistical, predictive, optimization, machine learning, and AI solutions to address business and design challenges, driving end-to-end project ownership.
Compensation
Compensation for this role is based upon experience, qualifications, location, and education and typically ranges from $140,000 to $160,000.
Responsibilities
Develop and implement statistical, predictive, optimization, machine learning, and AI solutions that address meaningful business and design challenges.
Independently drive data science projects from problem discovery and data exploration through modeling, validation, deployment, and adoption.
Define scope, identify risks and dependencies, and break ambiguous problems into concrete deliverables.
Build, validate, and evaluate predictive and statistical models using rigorous analytical methods.
Develop analytical and machine learning solutions with production use in mind, including reproducibility, testing, versioning, deployment, and maintainability.
Requirements
Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering or related quantitative field
Seeking a scientifically-minded Data Scientist to help R&D teams capture the value of the Uncountable platform, working hands-on with visualization, statistics, and machine-learning tools to design design-of-experiments (DoE) studies and drive formulation, and process optimization.
Locations (2)
Hsinchu County, Hsinchu County, Taiwan
Hsinchu City, Hsinchu City, Taiwan
Responsibilities
Partner directly with R&D teams to understand their scientific challenges, data, and experimentation workflows, then translate them into DoE and optimization studies on the Uncountable platform.
Use the platform’s visualization, statistical, and machine-learning tools to explore experimental data, surface key drivers and relationships, and recommend the next best experiments.
Master the Uncountable platform and turn its capabilities into measurable wins for R&D.
Develop analytical capabilities beyond the platform — extending the impact of data science across the R&D organization.
Competitive salary. We hold high expectations, but pay accordingly.
Responsibilities
Design, build, and maintain software products and data science models capable of simulating or predicting key components, properties and events of electricity grids, including individual connections to the grid such as power assets, commercial, industrial, agricultural and infrastructure projects
Machine Learning — PhD Intern (Modeling and Data Analysis)
This internship focuses on machine learning surrogate models for engineering simulation and measurement. The intern will design, train, and evaluate neural surrogate models to predict engineering responses from simulation or measurement data faster than repeated high-fidelity simulation.
Compensation
(PhD) $51-$56
Responsibilities
Generate parametric engineering datasets using simulation and/or measurement sources, with attention to sampling strategy and to numerical noise in the underlying data.
Design, train, and evaluate neural surrogate models for engineering response prediction.
Investigate how the choice of output representation affects accuracy, particularly across operating regions or frequency ranges where the response varies sharply.
Establish rigorous baselines and quantify accuracy as a function of simulation or measurement budget.
Evaluate LoRA and related parameter-efficient methods for specializing trained models to new problem settings, against full and partial fine-tuning.
Lead R&D development and integration of ink and printhead solutions for HP’s PageWide Industrial business, combining hands‑on experimentation, system design, and advanced problem solving to advance technology from ideation to product introduction.
Compensation
The pay range for this role is $93,400 to $143,800 USD annually with additional opportunities for pay in the form of bonus and/or equity (applies to United States of America candidates only). Pay varies by work location, job-related knowledge, skills, and experience.
Responsibilities
Lead R&D development and integration of ink and printhead solutions
Partner with ink chemists to optimize formulations for print quality and system compatibility
Collaborate with printhead, silicon, and fluidic-design teams to optimize microfluidic designs and firing conditions
Translate product and program needs into system requirements, performance metrics, acceptance criteria, and technical milestones
Define and evolve characterization methods, failure criteria, measurement systems, and accelerated tests
Requirements
Four‑year or Graduate Degree in Electrical Engineering, or any other related discipline or commensurate work experience or demonstrated competence
Obtain data from disparate sources to inform and support modelling, by performing data discovery and/or developing automated retrieval pipelines as needed
Ensure software and model capabilities, coverage and performance align with customer requirements, directly engaging with customers from time to time in order to do so
Collaborate with Software Engineers, Data Engineers, and other Product teams to understand data science requirements and translate them into technical solutions
Establish best practices for development, validation, and monitoring of data and software products
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