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Below is what you will be doing to drive improvements to our parts forecasting processes:
Become a subject matter expert on our customer demand data environment:
Understand the complexities and context around customer spare parts demand, situational factors such as customer contract entitlements, demand priority, product type, etc.
Understand the associations of various parts and the respective products they belong to, which facilitates a mapping of where every unit in operation
Identify problematic data records and anomalies that need to be resolved with data systems teams
Build customer demand rate models to identify any variability across the fleet
Identify any statically meaningful demand rate variation across customers, product types, customer entitlements, etc (and any combination thereof)
Build bottoms up part forecasts across the fleet as a function of these customer demand rate models
Work with demand frequency and volatility segmentation techniques to establish risk profiles for parts with unpredictable pattern
Collaborate with other data scientists to input all the above data elements into various machine learning models designed to predict and optimize our customer experience
Preferred Qualifications:
Manufacturing, Supply Chain, or related industry experience
Minimum Qualifications
Bachelor’s degree with +5 years’ work experience, OR Master’s degree with +3 years’ work experience
Educational background in Data Science, Data Analytics, IT or related field
Strong data wrangling skills to extract and craft complex data into a usable format
Strong skills with SQL, Python and/or R
Experience with statistical / regression / ML modeling
Ability to quickly learn new/differentlanguages/technologies/etc
Communicate technical information to management and non-technical business partners
Ability to collaborate closely with team members and cross functional domain experts to share knowledge and interconnect solutions
or at +1-408-352-2808
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Research and test new optical technologies for wafer inspection implementations.
Conceive new concepts based on solid physics understanding of light and material interaction and imaging theory.
Validate concepts through modeling, simulations and experiments.
Design and build optical imaging test benches for technology feasibility study.
Design and conduct experiments, collect and analyze data, draw clear conclusions from multivariable data sets.
Qualifications:
We seek candidates with a PhD in Physics, Material Science, Electrical Engineering or related fields.
Experienced user of Matlab, familiar with Zemax.
Doctorate (Academic) Degree and 0 years related work experience; Master's Level Degree and related work experience of 3 years; Bachelor's Level Degree and related work experience of 5 years.PhD in Physics, Material Science, Electrical Engineering or related fields.
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These jobs might be a good fit

Share
These jobs might be a good fit

Share
These jobs might be a good fit

Share
Responsibilities in this role include:
Minimum Qualifications
Doctorate (Academic) Degree and 0 years related work experience; Master's Level Degree and related work experience of 3 years.
or at +1-408-352-2808
These jobs might be a good fit

Share
Below is what you will be doing to drive improvements to our parts forecasting processes:
Become a subject matter expert on our customer demand data environment:
Understand the complexities and context around customer spare parts demand, situational factors such as customer contract entitlements, demand priority, product type, etc.
Understand the associations of various parts and the respective products they belong to, which facilitates a mapping of where every unit in operation
Identify problematic data records and anomalies that need to be resolved with data systems teams
Build customer demand rate models to identify any variability across the fleet
Identify any statically meaningful demand rate variation across customers, product types, customer entitlements, etc (and any combination thereof)
Build bottoms up part forecasts across the fleet as a function of these customer demand rate models
Work with demand frequency and volatility segmentation techniques to establish risk profiles for parts with unpredictable pattern
Collaborate with other data scientists to input all the above data elements into various machine learning models designed to predict and optimize our customer experience
Preferred Qualifications:
Manufacturing, Supply Chain, or related industry experience
Minimum Qualifications
Bachelor’s degree with +5 years’ work experience, OR Master’s degree with +3 years’ work experience
Educational background in Data Science, Data Analytics, IT or related field
Strong data wrangling skills to extract and craft complex data into a usable format
Strong skills with SQL, Python and/or R
Experience with statistical / regression / ML modeling
Ability to quickly learn new/differentlanguages/technologies/etc
Communicate technical information to management and non-technical business partners
Ability to collaborate closely with team members and cross functional domain experts to share knowledge and interconnect solutions
or at +1-408-352-2808
These jobs might be a good fit