Data Scientist

Jabil•Austin, KY

About The Position

At Jabil we strive to make ANYTHING POSSIBLE and EVERYTHING BETTER. We are proud to be a trusted partner for the world's top brands, offering comprehensive engineering, manufacturing, and supply chain solutions. With over 50 years of experience across industries and a vast network of over 100 sites worldwide, Jabil combines global reach with local expertise to deliver both scalable and customized solutions. Our commitment extends beyond business success as we strive to build sustainable processes that minimize environmental impact and foster vibrant and diverse communities around the globe. We are seeking a highly analytical and customer-focused Data Scientist with a strong industry experience in compute server/rack with a test or quality engineering background. This role is ideal for someone who thrives on solving complex problems through data and can translate customer needs into actionable insights. The successful candidate will work closely with engineering and site leadership to accelerate decision-making and drive continuous improvement.

Requirements

Bachelor’s degree in a technical field, such as Electrical Engineering, Information Technology, Data Science, or a related discipline. A combination of education and equivalent experience may be considered on a case-by-case basis.
Strong background in test or quality engineering is a must.
Proven ability to listen to customer needs, define complex requirements, and deliver data solutions.
Experience with Power BI, Kibana, Elastic Search, and open-source analytics tools.
Proficiency in Office Suite, including advanced Excel and Minitab.
Solid understanding of server/rack assembly and test processes.
Strong written and verbal communication skills; multi-lingual capability is a plus.
Ability to work effectively in teams and under pressure.
Demonstrated ability to build business cases and drive measurable outcomes.
Highly motivated, creative, and capable of thinking “outside the box.”

Responsibilities

Collaborate with customers and internal stakeholders to understand business challenges and define data requirements.
Read and interpret production process documentation (e.g., flow charts, FMEAs) and adapt raw data to reflect real-world production processes.
Build and validate queries to extract meaningful insights from complex datasets.
Characterize data distributions using statistical tools (mean, median, standard deviation, skewness, etc.).
Use programming logic tools (e.g., Boolean logic: AND, OR, NOR, NAND, XOR; If > Then statements) to support data analysis and automation.
Analyze and interpret data to identify trends, patterns, and opportunities for improvement.
Transform raw data into actionable knowledge using advanced analytics techniques.
Develop predictive models and simulations using methods such as time series analysis, multivariate analysis, constraint programming, and pattern recognition.
Create compelling dashboards and visualizations using Power BI, Kibana, and Elastic Search.
Use Minitab to validate statistical tests between samples and support quality improvement initiatives.
Leverage advanced Excel functions and features for data manipulation and reporting.
Present business cases and recommendations to technical and non-technical audiences.
Create and maintain project timelines and budget plans to support platform evolution.
Interface with all levels of the organization, from shop floor personnel to upper management.