Location: Stuttgart, Germany
Shift Work: No (Standard Day Shift)
Clearance Requirement: Active TS/SCI with CI Polygraph Eligibility
At Praescient Analytics, we provide cutting-edge advanced analytics, intelligence training, and technology integration to solve the world's most complex security challenges. We are looking for an analytical Senior Data Scientist to join our high-performing team in Stuttgart, Germany.
If you have a passion for data science, machine learning, and a drive to support critical national security missions, we want to hear from you.
*Relocation assistance is available.*
As a Senior Data Scientist, you will leverage advanced quantitative methodologies, machine learning models, and automated Python workflows to deliver deep analytical insights. Working in a collaborative, mission-focused environment, you will prepare complex datasets, perform data quality assurance, build interactive dashboards, and conduct advanced unstructured data analysis.
Praescient Analytics is a Certified Woman-Owned Small Business (WOSB) with over a decade of expertise in advanced analytics, engineering, and DevOps, specializing in transforming complex data into actionable intelligence for informed decision-making. Since 2011, we have supported over 40 organizations across diverse domains, including military intelligence operations, financial and fraud investigations, and insider threat detection.
Our team of experts - skilled in cloud computing, artificial intelligence, machine learning, data science, DevOps, and engineering - brings deep experience in solving complex challenges. With a proven track record in federal contracting, we deliver tailored, high-impact solutions designed to enhance operational efficiency, ensure mission success, and address the evolving needs of our clients. Praescient's innovative and adaptive approach makes us a trusted partner in delivering data-driven insights and technological excellence for critical missions.
#J-18808-LjbffrVeröffentlichungsdatum:
09 Aug 2026Standort:
StuttgartTyp:
VollzeitArbeitsmodell:
Vor OrtKategorie:
Erfahrung:
2+ yearsArbeitsverhältnis:
Angestellt
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